From dorien.herremans at gmail.com Thu Oct 1 02:47:28 2020 From: dorien.herremans at gmail.com (Dorien Herremans) Date: Thu, 1 Oct 2020 14:47:28 +0800 Subject: Connectionists: nnAudio - new Open Source library for GPU-based on the fly audio processing in PyTorch Message-ID: Dear community, I am happy to present our *new library nnAudio *, which allows you to feed waveforms directly into a PyTorch neural network. Our nnAudio layer converts the waveforms on the fly to spectrograms (linear, log, Mel, CQT), and even offers a trainable (Fourrier) kernel. So no more storing large batches of spectrogram images and preprocessing, we obtain speeds 100x faster then traditional processing, plus you can finetune the spectrogram to your task through training. More info on how to use nnAudio: https://github.com/KinWaiCheuk/nnAudio If you are interested to become a *contributor* to nnAudio to help with the feature request we have been receiving from our rapidly growing user base, let me know! More info in our publication: *K. W. Cheuk, H. Anderson, K. Agres and D. Herremans, "nnAudio: An on-the-fly GPU Audio to Spectrogram Conversion Toolbox Using 1D Convolutional Neural Networks," in IEEE Access, doi: 10.1109/ACCESS.2020.3019084. *https://ieeexplore.ieee.org/document/9174990 *In this paper, we present nnAudio , a new neural network-based audio processing framework with graphics processing unit (GPU) support that leverages 1D convolutional neural networks to perform time domain to frequency domain conversion. It allows on-the-fly spectrogram extraction due to its fast speed, without the need to store any spectrograms on the disk. Moreover, this approach also allows back-propagation on the waveforms-to-spectrograms transformation layer, and hence, the transformation process can be made trainable, further optimizing the waveform-to-spectrogram transformation for the specific task that the neural network is trained on. All spectrogram implementations scale as Big-O of linear time with respect to the input length. nnAudio , however, leverages the compute unified device architecture (CUDA) of 1D convolutional neural network from PyTorch , its short-time Fourier transform (STFT), Mel spectrogram, and constant-Q transform (CQT) implementations are an order of magnitude faster than other implementations using only the central processing unit (CPU). We tested our framework on three different machines with NVIDIA GPUs, and our framework significantly reduces the spectrogram extraction time from the order of seconds (using a popular python library librosa ) to the order of milliseconds, given that the audio recordings are of the same length. When applying nnAudio to variable input audio lengths, an average of 11.5 hours are required to extract 34 spectrogram types with different parameters from the MusicNet dataset using librosa . An average of 2.8 hours is required for nnAudio , which is still four times faster than librosa . Our proposed framework also outperforms existing GPU processing libraries such as Kapre and torchaudio in terms of processing speed.* -- Dorien Herremans, PhD Assistant Professor http://dorienherremans.com Singapore University of Technology and Design Information Technology and Design Pillar Office 1.502-18 -------------- next part -------------- An HTML attachment was scrubbed... URL: From chabane.djeraba at univ-lille.fr Thu Oct 1 04:09:25 2020 From: chabane.djeraba at univ-lille.fr (Chaabane Djeraba) Date: Thu, 1 Oct 2020 10:09:25 +0200 (CEST) Subject: Connectionists: CFP - Content-Based Multimedia Indexing - 2021 - Lille - France In-Reply-To: <934382637.67902673.1601492534907.JavaMail.zimbra@univ-lille.fr> References: <1085569528.65496237.1601447618624.JavaMail.zimbra@univ-lille.fr> <1602737029.67216506.1601473325226.JavaMail.zimbra@univ-lille.fr> <934382637.67902673.1601492534907.JavaMail.zimbra@univ-lille.fr> Message-ID: <1539676708.68213757.1601539765678.JavaMail.zimbra@univ-lille.fr> Special session: Bio-inspired circuits, systems and algorithms for multimedia CBMI2021 aims at bringing together the various communities involved in all aspects of content-based multimedia indexing for retrieval, browsing, management, visualization and analytics. The Special Session on bio-inspired circuits, systems and algorithms will be a mini-venue, focusing on the state-of-the-art and research direction of the emerging field of bio-inspired circuits, systems and algorithms and in the envisioned applications and breakthrough that the application of this bioinspired technology and algorithms can bring to the content-based multimedia indexing field development. Special session papers, which can be invited or submitted, will supplement the regular research papers and be included in the proceedings of CBMI 2021. The special session would include four to five papers, which can be invited, or regular submissions. In order to ensure the high quality of all conference papers, all papers submitted to special session will be peer-reviewed through the standard review process, including invited papers. If the special session has many high-quality submissions, some of the submissions may potentially be moved to some regular sessions. Authors are encouraged to submit previously unpublished research papers including bioinspired circuits, systems and algorithms that address the use of the bioinspired technology and algorithms in the areas of search and retrieval, multimedia content management, user interaction, large-scale search, learning in retrieval, social media indexing and retrieval, surveillance and security. Other applications areas of interest to the CBMI community not listed above maybe considered. ORGANIZERS: Teresa Serrano Gotarredona, IMSE-CNM ? terese at imse-cnm.csic.es DATES + STUDENT participation see bellow. ----oooOooo---- CONTENT-BASED MULTIMEDIA INDEXING University of Lille, Cit? scientifique, Villeneuve d?Ascq, France, 28-30 June 2021 cbmi2021.univ-lille.fr CBMI (eighteenth edition) aims at bringing together the various communities involved in all aspects of content-based multimedia indexing for retrieval, browsing, management, visualization and analytics. Topics of interest to the CBMI community include, but are not limited to, the following: audio and visual and multimedia indexing, multimodal and cross-modal indexing, deep learning for multimedia indexing, visual content extraction, audio (speech, music, etc.) content extraction, identification and tracking of semantic regions and events, social media analysis? The eighteenth edition of CBMI will be organized by the CRIStAL laboratory at University of Lille, Lille, France, following the successful previous editions of Toulouse 1999, Brescia 2001, Rennes 2003, Riga 2005, Bordeaux 2007, London 2008, Chania 2009, Grenoble 2010, Madrid 2011, Annecy 2012, Veszprem 2013, Klagenfurt 2014, Prague 2015, Bucharest 2016, Firenze 2017, La Rochelle 2018, and Dublin 2019. Authors are encouraged to submit previously unpublished research papers in the broad field of content-based multimedia indexing and applications. We wish to highlight significant contributions addressing the main problem of search and retrieval but also the related and equally important issues of multimedia content management, user interaction, large-scale search, learning in retrieval, social media indexing and retrieval. Additional special sessions are planned in areas such as deep learning for retrieval, social media retrieval, cultural heritage, surveillance and security. Authors can submit full length (6 pages - to be presented as oral presentation) or short papers (4 pages - to be presented as posters). Papers can be submitted to the regular paper sessions, demo session, or to one of the special sessions. Additionally demonstration papers (up to 4 pages) may also be submitted that highlight interesting and novel demos of CBMI-related technologies. The submissions are peer reviewed in a single blind process. The language of the conference is English. The CBMI 2020 conference adheres to the IEEE paper formatting guidelines. When preparing your submission, please follow the IEEE guidelines given by IEEE at the Manuscript Templates for Conference Proceedings. The CBMI proceedings are traditionally indexed and distributed by IEEE Xplore and ACM DL. In addition, authors of certain best papers of the conference will be invited to submit extended versions of their contributions to a special issue of a leading journal in the field (e.g. MTAP - Springer), and other best papers will be invited to submit extended versions of their contributions in a book (ISTE/WILEY publisher). Topics of interest to the CBMI community include, but are not limited to, the following: ? Audio and visual and multimedia indexing ? Multimodal and cross-modal indexing ? Deep learning for multimedia indexing ? Visual content extraction ? Audio (speech, music, etc) content extraction ? Identification and tracking of semantic regions and events ? Social media analysis ? Metadata generation, coding and transformation ? Multimedia information retrieval (image, audio, video, text) ? Mobile media retrieval ? Event-based media processing and retrieval ? Affective/emotional interaction or interfaces for multimedia retrieval ? Multimedia data mining and analytics ? Multimedia recommendation ? Large scale multimedia database management ? Summarization, browsing and organization of multimedia content ? Personalization and content adaptation ? User interaction and relevance feedback ? Multimedia interfaces, presentation and visualization tools ? Evaluation and benchmarking of multimedia retrieval systems ? Applications of multimedia retrieval, e.g., medicine, lifelogs, satellite imagery, video surveillance ? Cultural heritage applications DATES: Conference date : 28-30 June 2021, at Lille, France. Contact: cbmi2021-organisation at univ-lille.fr Deadline for regular paper and demo submissions : 15 January 2021 Notification of acceptance : 15 March 2021 Camera-ready papers due : 30 March 2021 STUDENT PARTICIPATION: We strongly encourage students to participate in CBMI-21 event and submit their research. We strongly believe in their power and they are the future of the research in content-based multimedia indexing. For these reasons and for the first time in the history of the conference, the 2021 edition of CBMI with support of ACM SIGMM (www.sigmm.org), will sponsor several students, authors of papers submitted and accepted by CBMI-21, and being corresponding author of a paper. The student status will be recognized only to PhDs and master students. Certain students will be totally sponsored, including registration fees, accommodations and travel expenses. Other students will be partly sponsored, including substantial reduction in the registration fees, no cut-backs to the students? conference experience, and budget accommodation options and arrangement for room sharing. Furthermore, in this edition, prizes will be awarded to the best student poster presentations of CBMI2021. All the participants registered to CBMI2021 as student will be automatically admitted to the selection for the awards. All the papers accepted as poster presentation by the Technical Program Committee (TPC), from students will be considered for the awards, given that a full-paper manuscript has been submitted. The student poster awards committee will evaluate the nominated contributions during the poster sessions of CBMI2021. The evaluation criteria will be independently established by the Committee before the conference and will take into account the scientific content as well as the technical quality of the posters. The Student Poster Awards will be announced during the Gala Dinner, on June 29th. ----oooOooo---- From vishal.pup at gmail.com Thu Oct 1 04:52:10 2020 From: vishal.pup at gmail.com (=?UTF-8?B?VmlzaGFsIEdveWFsKOCkteCkv+CktuCkvuCksiDgpJfgpYvgpK/gpLIp?=) Date: Thu, 1 Oct 2020 14:22:10 +0530 Subject: Connectionists: Co-located Event with ICON 2020, IIT Patna In-Reply-To: References: Message-ID: Dear All, Greetings. Please find this weblink to know details about an event co-located with ICON 2020 organized by IIT Patna on 18-20 December 2020. This co-located event is basically showcasing your NLP tool and sharing your resources with the NLP research community. There are no registration fees for participating in this event. Come forward and share your NLP tools with the NLP Community. https://www.iitp.ac.in/~ai-nlp-ml/icon2020/resources/Call%20for%20Demonstration-ICON%202020.pdf > > -- *Regards,* Dr. Vishal Goyal, Professor, Department of Computer Science, State Awardee (Two Times) Deputy Director, Centre for E-Learning and Teaching Excellence Coordinator, Research Centre for Technologies Development for Differently Abled Persons Coordinator, Centre for Research in Artificial Intelligence and Data Science Coordinator, iHRMS implementation team Nodal officer, GeM Operations Nodal Officer, NPTEL Local Chapter Punjabi University Patiala-147002. Mobile:+919501096111 Email - vishal.pup at gmail.com,vishal_cs at pbi.ac.in -------------- next part -------------- An HTML attachment was scrubbed... URL: From fabio.bellavia at unifi.it Thu Oct 1 06:12:53 2020 From: fabio.bellavia at unifi.it (Fabio Bellavia) Date: Thu, 1 Oct 2020 12:12:53 +0200 Subject: Connectionists: CfP - FAPER2020@ICPR2020 - UPDATES: switching to online mode and deadline extended! In-Reply-To: References: Message-ID: ???????????????????? FAPER2020 workshop at ICPR2020 ???????????? ---===== Apologies for cross-postings =====--- ?????????? Please distribute this call to interested parties _______________________________________________________________________ ?International Workshop on Fine Art Pattern Extraction and Recognition ????????????????????????? F A P E R?? 2 0 2 0 ??????????????????? workshop in conjunction with the ??? 25th International Conference on Pattern Recognition (ICPR2020) ???????????????????? Milan, Italy, January 11, 2021 ???????? >>> https://sites.google.com/view/faper-workshop/ <<< ??? //???????? S U B M I S S I O N??? D E A D L I N E??????? \\ ??? \\?? E X T E N D E D??? T O??? 1 7??? O C T O B E R !!!? // ?????? +++ UPDATES: the workshop will be taken FULLY VIRTUAL +++ ??? * PLEASE NOTE THAT PAPERS NOT ACCEPTED IN THE ICPR2020 GENERAL * ????? SESSION AND FITTING FAPER2020 TOPICS COULD BE SUBMITTED HERE ??? -----> https://easychair.org/conferences/?conf=faper2020 <----- _______________________________________________________________________ === Aim & Scope === Cultural heritage, in particular fine art, has invaluable importance for the cultural, historic, and economic growth of our societies. Fine art is developed primarily for aesthetic purposes, and it is mainly concerned with paintings, sculptures, and architectures. In the last few years, due to technology improvements and drastically declining costs, a large-scale digitization effort has been made, leading to a growing availability of large digitized fine art collections. This availability, along with the recent advancements in pattern recognition and computer vision, has opened new opportunities for computer science researchers to assist the art community with automatic tools to analyse and further understand fine arts. Among the other benefits, a deeper understanding of fine arts has the potential to make them more accessible to a wider population, both in terms of fruition and creation, thus supporting the spread of culture. The ability to recognize meaningful patterns in fine art inherently falls within the domain of human perception, and this perception can be extremely hard to conceptualize. Thus, visual-related features, such as those automatically learned by deep learning models, can be the key to tackling problems of extracting useful representations from low-level colour and texture features. These representations can assist in various art-related tasks, ranging from object detection in paintings to artistic style categorization, useful for examples in museum and art gallery websites. The aim of the workshop is to provide an international forum for those who wish to present advancements in the state of the art, innovative research, ongoing projects, and academic and industrial reports on the application of visual pattern extraction and recognition for the better understanding and fruition of fine arts. The workshop solicits contributions from diverse areas such as pattern recognition, computer vision, artificial intelligence and image processing. === Topics === Topics of interest include, but are not limited to: - Application of machine learning and deep learning to cultural heritage - Computer vision and multimedia data - Generative adversarial networks for artistic data - Augmented and virtual reality for cultural heritage - 3D reconstruction of historical artifacts - Historical document analysis - Content-based retrieval in the art domain - Speech, audio and music analysis from historical archives - Digitally enriched museum visits - Smart interactive experiences in cultural sites - Projects, products or prototypes for cultural heritage restoration, preservation and fruition === Invited Speaker === Fabio Remondino (3DOM|FBK, Italy) Dr. Fabio Remondino is the head of the 3D Optical Metrology (http://3dom.fbk.eu) research unit at FBK - Bruno Kessler Foundation (http://www.fbk.eu), a public research center located in Trento, Italy. His main research interests are in the field of reality-based surveying and 3D modeling, sensor and data fusion and 3D data classification. He is working in all automation aspects of the entire 3D reconstruction pipeline for applications in the industrial, environmental and heritage field. He is author of more than 200 articles in journals and conferences. He is involved in knowledge and technology transfer, organizing more than 30 conferences, 20 summerschools and 5 tutorials. Fabio is currently serving as President of the ISPRS Technical Commission II (http://www.isprs.org) and Vice-President of EuroSDR (http://eurosdr.net). He was vice-President of CIPA Heritage Documentation (https://www.cipaheritagedocumentation.org/) from 2015 to 2019. === Important Dates === -? October? 17th 2020 - workshop submission deadline (*EXTENDED*) -? November 10th 2020 - author notification -? November 15th 2020 - camera-ready submission -? December? 1st 2020 - finalized workshop program === Submission Guidelines === Submissions must be formatted in accordance with the Springer's Computer Science Proceedings guidelines. The following paper categories are welcome: - Full papers (12-15 pages, including references) - Short papers? (6-8 pages, including references) Accepted manuscripts will be included in the ICPR 2020 Workshop Proceedings Springer volume. Once accepted, at least one author is expected to attend the event and orally present the paper. *** Due to the COVID pandemic, the workshop will be taken fully virtual. All accepted papers will be published. *** === FAPER 2020 Special Issue === Authors of selected papers will be invited to extend and improve their contributions in the Special Issue "Fine Art Pattern Extraction and Recognition" of the Journal of Imaging (MDPI). - https://www.mdpi.com/journal/jimaging/special_issues/faper2020 - === Organizing committee === Gennaro Vessio (University of Bari, Italy) Giovanna Castellano (University of Bari, Italy) Fabio Bellavia (University of Palermo, Italy) _________________________________________________________ ?Contacts: gennaro.vessio at uniba.it ?????????? giovanna.castellano at uniba.it ?????????? fabio.bellavia at unipa.it ?Workshop: https://sites.google.com/view/faper-workshop/ ?ICPR2020: https://www.micc.unifi.it/icpr2020/ From fabio.bellavia at unifi.it Thu Oct 1 06:13:25 2020 From: fabio.bellavia at unifi.it (Fabio Bellavia) Date: Thu, 1 Oct 2020 12:13:25 +0200 Subject: Connectionists: CFP - MAES@ICPR2020 workshop - UPDATES: online rescheduling and deadline extended! Message-ID: <43e98415-b056-d981-8bb9-91d10d9315f8@unifi.it> ???????????????????? MAES2020 workshop at ICPR2020 ?????????? ---===== Apologies for multiple posting =====--- ?????????? Please distribute this call to interested parties _______________________________________________________________________ ??? Machine Learning Advances Environmental Science (MAES at ICPR2020) ??????????????????????????? workshop at the ??? 25th International Conference on Pattern Recognition (ICPR2020) ???????????????????? Milan, Italy, January 10, 2021 ????????? >>> https://sites.google.com/view/maes-icpr2020/ <<< ??? //?????????? S U B M I S S I O N??? D E A D L I N E?????????? \\ ??? \\??? E X T E N D E D??? T O??? 2 5??? O C T O B E R !!!????? // ?????? +++ UPDATES: the workshop will be taken FULLY VIRTUAL +++ ??? * PLEASE NOTE THAT PAPERS NOT ACCEPTED IN THE ICPR2020 GENERAL * ?????? SESSION AND FITTING MAES TOPICS COULD BE SUBMITTED HERE !!! ??? ----> https://easychair.org/conferences/?conf=maesicpr2020 <---- _______________________________________________________________________ ?=== Aim & Scope === Environmental data are growing steadily in volume, complexity and diversity to Big Data mainly driven by advanced sensor technology. Machine learning can offer superior techniques for unravelling complexity, knowledge discovery and predictability of Big Data environmental science. The aim of the workshop is to provide a state-of-the-art survey of environmental research topics that can benefit from Machine Learning methods and techniques. To this purpose the workshop welcomes papers on successful environmental applications of machine learning and pattern recognition techniques to? diverse domains of Environmental Research, for instance, recognition of biodiversity in thermal, photo and acoustic images, natural hazards analysis and prediction, environmental remote sensing, estimation of environmental risks, prediction of the concentrations of pollutants in geographical areas, environmental threshold analysis and predictive modelling, estimation of Genetical Modified Organisms (GMO) effects on non-target species. The workshop will be the place to make an analysis of the advances of Machine Learning for the Environmental Science and should indicate the open problems in environmental research that still have not properly benefited from Machine Learning. Extended papers of this workshop will be published as a special issue in the journal of Environmental Modelling and Software, Elsevier. *** Due to the COVID pandemic, the workshop will be taken fully virtual. All accepted papers will be published. *** ?=== Invited Talk === "Harnessing big environmental data by machine learning", prof. Friedrich Recknagel, School of Biological Sciences, University of Adelaide, Australia (prof. Recknagel's bio: http://www.adelaide.edu.au/directory/friedrich.recknagel) (talk abstract: https://drive.google.com/file/d/12BFBiG4pwN-6TRKCy0OuGHOgue4YbOKJ/view?usp=sharing) ?=== Important Dates === -? 25 October? 2020 - workshop submission deadline (*EXTENDED*) -? 10 November 2020 - author notification -? 15 November 2020 - camera-ready submission -?? 1 December 2020 - finalized workshop program ?=== Organizers === ? Francesco Camastra, Universita' di Napoli Parthenope, Italy ?Friedrich Recknagel, University of Adelaide, Australia ??? Antonino Staiano, Universita' di Napoli Parthenope, Italy ?== Publicity chair == ????? Fabio Bellavia, Universita' di Palermo, Italy _______________________________________________________________________ ?Contacts: antonino.staiano at uniparthenope.it ?????????? francesco.camastra at uniparthenope.it ?Workshop: https://sites.google.com/view/maes-icpr2020/ ?ICPR2020: https://www.micc.unifi.it/icpr2020/ From claudio.piciarelli at uniud.it Fri Oct 2 06:15:08 2020 From: claudio.piciarelli at uniud.it (Claudio Piciarelli) Date: Fri, 2 Oct 2020 10:15:08 +0000 Subject: Connectionists: CFP - Remote Sensing - Special Issue on Computer Vision and Deep Learning for Remote Sensing Applications Message-ID: (apologies for multiple copies) =================================================================== CALL FOR PAPERS * Special Issue on Computer Vision and Deep Learning for Remote Sensing Applications * Journal: Remote Sensing (MDPI), IF 4.118 Guest Editors: Hyungtae Lee, Sungmin Eum, Claudio Piciarelli Full info: http://mdpi.com/si/46402 Deadline: accepted papers will be published continuously (as soon as accepted) till the deadline (31 March 2021) =================================================================== Abstract: Today, the field of computer vision and deep learning is rapidly progressing into many applications, including remote sensing, due to its remarkable performance. Especially for remote sensing, a myriad of challenges due to difficult data acquisition and annotation have not been fully solved yet. The remote sensing community is waiting for a breakthrough to address these challenges by utilizing high-performance deep learning-based models that typically require large-scale annotated datasets. This issue is looking for such breakthroughs focusing on the advances in remote sensing using computer vision, deep learning and artificial intelligence. Although broad in scope, contributions with a specific focus are expected. For this special issue, we welcome the most recent advancements related, but not limited to: * Deep learning architecture for remote sensing * Machine learning for remote sensing * Computer vision method for remote sensing * Classification / Detection / Regression * Unsupervised feature learning for remote sensing * Domain adaptation and transfer learning with computer vision and deep learning for remote sensing * Anomaly/novelty detection for remote sensing * New dataset and task for remote sensing * Remote sensing data analysis * New remote sensing application * Synthetic remote sensing data generation * Real-time remote sensing * Deep learning-based image registration Dr. Hyungtae Lee Dr. Sungmin Eum Dr. Claudio Piciarelli Guest Editors -------------- next part -------------- An HTML attachment was scrubbed... URL: From Albrecht_Zimmermann at gmx.net Fri Oct 2 08:15:23 2020 From: Albrecht_Zimmermann at gmx.net (Albrecht Zimmermann) Date: Fri, 2 Oct 2020 14:15:23 +0200 Subject: Connectionists: [SDM21] last call for papers Message-ID: An HTML attachment was scrubbed... URL: From eric.dewitt at neuro.fchampalimaud.org Fri Oct 2 11:07:53 2020 From: eric.dewitt at neuro.fchampalimaud.org (Eric DeWitt) Date: Fri, 2 Oct 2020 16:07:53 +0100 Subject: Connectionists: Announcing the 2020 CCN GAC kickoff workshops! (Please RSVP!) Message-ID: <3958C80D-FF45-4887-9A7D-2ED5273C7890@neuro.fchampalimaud.org> Dear Connectionist Community, This year the Cognitive Computational Neuroscience cancelled it?s in person conference scheduled for August 2020 and launched a new, unique project: The CCN Generative Adversarial Collaborations (see the announcement here: https://gac.ccneuro.org/). The goal is to generate bring together a diverse group of researchers to clarify a controversy or outstanding open question and propose concrete steps (experimental and theoretical) to help resolve it. The kickoff workshops for the 2020 CCN GACs have been scheduled! There will be six open workshops, spanning October 15-23, with the entire community invited to attend and participate! The goals is to help move the current GAC initial proposals forward and allow other interested members of the community to engage. See the full schedule here: https://gac.ccneuro.org/schedule If you are planning to come to the virtual workshops, please help us plan for capacity by filling out this RSVP form. https://docs.google.com/forms/d/e/1FAIpQLSf47xOjBgcOUqEdM35egCATquq3kb9cV91AkkLSQ0TA7nh_Pg/viewform?usp=sf_link We hope to see you there! - the CCN Program Committee: Gunnar Blohm, Eric DeWitt, Ralf Haefner, Niko Kriegeskorte, Jennifer Lieberman, Megan Peters, & Gemma Roig Email questions to gac at ccneuro.org From terry at snl.salk.edu Fri Oct 2 13:33:58 2020 From: terry at snl.salk.edu (Terry Sejnowski) Date: Fri, 2 Oct 2020 10:33:58 -0700 Subject: Connectionists: Misha Mahowald Prize 2020 In-Reply-To: <3f017dce-62d4-293d-66bb-ddb042ccc245@snl.salk.edu> References: <3f017dce-62d4-293d-66bb-ddb042ccc245@snl.salk.edu> Message-ID: Reminder: Misha Mahowald Prize 2020 image The Misha Mahowald Prize recognizes outstanding research in neuromorphic engineering. The Prize is named for the late Misha Mahowald, one of the most influential pioneers of the field of neuromorphic engineering. The award is considered annually. The competition is open to any individual or research group worldwide. The Prize is for a project, not persons. Entries will likely to fall into one or more of the following categories: * a neuromorphic circuit, device or system * a neuromorphic algorithm or operating principle * a tool which promotes the use of neuromorphic engineering technology The entry may be a summary of a published or unpublished paper, or a description of a project, product or service. Every project will be considered on its own merits, regardless of the development budget or the group who worked on it. We strongly encourage everyone who has developed a novel contribution to the field to enter, no matter how large or small the project. Projects can be submitted even if they are still in progress. They will be judged according to the results achieved at the time of submission. The submission of revised versions of projects that have been unsuccessful in previous years, is strongly encouraged. 2020 Prize * The value of the 2020 Prize will be $10'000. * The prize is decided by a Jury of internationally recognized experts under the chair of Prof. Terry Sejnowski * The submission document is limited to 4 A4 pages. This will be a brief description of the work: its novelty, _reality_, performance, and its potential impact. Include links to relevant images/tables/original papers, etc. * Details can be found here * The submission deadline is 23:59 UTC 31 October 2020. * The decision of the Jury concerning the 2019 Prize will be announced in December 2020. The prize is administered by /iniForum/, a Swiss association and events management company that promotes education, research and applications of brain-like computation. Contact: info at iniforum.ch -------------- next part -------------- An HTML attachment was scrubbed... URL: From tongzhang at ust.hk Mon Oct 5 01:57:54 2020 From: tongzhang at ust.hk (Tong ZHANG) Date: Mon, 5 Oct 2020 05:57:54 +0000 Subject: Connectionists: Faculty Positions in the Hong Kong University of Science and Technology (Guangzhou Campus) Message-ID: Dear colleagues, Faculty positions are available in the Hong Kong University of Science and Technology (Guangzhou Campus). Founding Faculty in the Information Hub The Hong Kong University of Science and Technology (HKUST) invites applications for founding faculty positions in Artificial Intelligence (AI) for its new campus in Guangzhou (GZ). HKUST(GZ) is interested in candidates at all ranks with a demonstrated ability to pursue high-impact research in AI, either in its algorithmic foundation, or in its translational applications. In addition to traditional AI related research areas such as machine learning, data mining, computer vision, natural language processing, we encourage candidates working in interdisciplinary research areas to apply. In particular, we look for candidates who can successfully apply AI to develop transformative technologies to improve our society, in fields such as media, design, finance, manufacturing, medicine, security, and smart living, etc. The Guangzhou/Shenzhen bay area is also one of the world?s most important technology hub with great potential for collaboration with the local industry and for commercialization of translational technology. We welcome senior candidates to apply, especially those who can help with the strategic development of the AI trust area for the new Guangzhou campus. This is a rare opportunity for candidates who want to influence the very early development of a top-ranked new university campus with endless potential for growth. Remuneration HKUST(GZ) offers highly competitive salary of international standard and will be commensurate with qualifications and experience. Generous research funds, ample laboratory space and excellent research equipment and support will be provided. Housing allowances will also be provided. Application Procedure Applications should be sent to > together with (i) full CV; (ii) a statement of research, teaching, and service; (iii) up to five most representative publications in PDF formats; (iv) record of teaching performance (if any); and (v) names and contact information of three referees. Applications will be evaluated as soon as they are received, and will receive full consideration until positions are filled. About the Information Hub The HKUST(GZ) Information Hub focuses on addressing global challenges arising from human interactions with information and technology in an era of digital transformation. The Hub is mainly comprised of four thrust areas: Artificial Intelligence, Data Science and Analytics, Future Communication Networks, and Digital Media and Arts. We have also established an Internet of Things (IoT) division focusing on technology transfer and industrial projects. In each of these areas, we are committed to providing a world-class education and conducting cutting-edge research with practical applications, with the purpose of becoming a world leader in information technology innovation and translation. About HKUST Guangzhou Campus [https://gz.ust.hk/] HKUST(GZ) offers a unique educational environment with four transdisciplinary hubs and 16 thrust areas. HKUST(GZ) offers superb research facilities, attracting top international faculty and students to conduct curiosity-driven and goal-oriented research to address the world?s pressing scientific and technological challenges. HKUST(GZ) is situated in Nansha District, Guangzhou, which is right in the center of the Greater Bay Area, one of the most vibrant and dynamic regions in the world, neighboring Shenzhen, Hong Kong, and Macao. It is about 30 minutes away from Hong Kong by high-speed train. The new campus is under construction and is planned to open in 2022. The successful candidate may start working on the Clear Water Bay campus in Hong Kong before the new campus is completed. ---- Tong Zhang -------------- next part -------------- An HTML attachment was scrubbed... URL: From bwyble at gmail.com Sat Oct 3 16:39:57 2020 From: bwyble at gmail.com (Brad Wyble) Date: Sat, 3 Oct 2020 16:39:57 -0400 Subject: Connectionists: Neuromatch Conference Deadline extension: Oct 7 Message-ID: Dear Neuroscience Community, Neuromatch Conference is pleased to announce that the deadline for abstract submission has been extended to October 7th, 2020. We have extended the abstract submission date to give you more time to prepare and submit your work so that you can form part of our wonderful neuroscience community by submitting at neuromatch.io Everything else remains unchanged! While the abstract deadline has been shifted, Neuromatch Conference is occurring between Oct. 26-30, 2020, and accepting abstracts from all areas of neuroscience, which have been divided into six main themes: Are you still unsure about what Neuromatch conference exactly is? We encourage you to watch this video by Dan Goodman (Imperial College London) on what Neuromatch Conference is, and why you should submit your work! As a reminder, Neuromatch Conference has a low cost of registration ($25) for both presenters and attendees. This fee can be waived if you cannot pay, for any reason. We would love to see you at Neuromatch Conference and hope that you will consider submitting your research. Best wishes, The Neuromatch Team Please follow our social media and visit our website for regular updates @Neuromatch @Neuromatch neuromatch.io -- Brad Wyble Associate Professor Psychology Department Penn State University http://wyblelab.com -------------- next part -------------- An HTML attachment was scrubbed... URL: From xiaochun.cheng at gmail.com Sun Oct 4 04:28:23 2020 From: xiaochun.cheng at gmail.com (Xiaochun Cheng) Date: Sun, 4 Oct 2020 09:28:23 +0100 Subject: Connectionists: Special Issue on Bio-inspired Computing - Emerging Theories and Industry Applications Message-ID: <001701d69a28$540f3360$fc2d9a20$@gmail.com> Welcome to submit your relevant original papers to the following special issue: Special Issue on Bio-inspired Computing - Emerging Theories and Industry Applications https://www.journals.elsevier.com/computers-and-electrical-engineering/call- for-papers/bio-inspired-computing-emerging-theories Submission of manuscript by Oct 26, 2020 Computers & Electrical Engineering, An International Journal https://www.journals.elsevier.com/computers-and-electrical-engineering [Our apologies if you receive multiple copies of this CFP] -------------- next part -------------- An HTML attachment was scrubbed... URL: From malini.vinita.samarasinghe at ini.rub.de Mon Oct 5 02:51:10 2020 From: malini.vinita.samarasinghe at ini.rub.de (Vinita Samarasinghe) Date: Mon, 5 Oct 2020 08:51:10 +0200 Subject: Connectionists: GEM2021 - Registration open Message-ID: Registration has opened! *GEM 2021**- Generative Episodic Memory: Interdisciplinary perspectives from psychology, neuroscience and philosophy* https://for2812.rub.de/gem2021 16-18 February 2021 The workshop will take place in virtual space and is free of charge. The main workshop will be preceded by a PhD symposium, for which submissions are now being accepted via EasyChair https://easychair.org/cfp/gem2021 Keynote Speakers: Karl-Heinz B?uml - University Regensburg, Germany Dorthe Berntsen - Aarhus University, Denmark Amy Criss - University of Syracuse, USA Dorothea Debus - University of Konstanz, Germany David Huber - University of Massachusetts, USA Sarah Robins - University of Kansas, USA Call for papers The DFG-funded research consortium ?FOR 2812 ? Constructing scenarios of the past? https://for2812.rub.de is proud to announce a call for papers for its first workshop on generative episodic memory. We invite submissions for talks and posters https://easychair.org/cfp/gem2021 . Episodic memories are widely regarded as memories of personally experienced events. Early concepts about episodic memory were based on the storage model, according to which experiential content is preserved in memory and later retrieved. However, overwhelming empirical evidence suggests that the content of episodic memory is ? at least to a certain degree ? constructed in the act of remembering. Even though very few contemporary researchers would oppose this view of episodic memory as a generative process, it has not become the standard paradigm of empirical memory research. This is particularly true for studies of the neural correlates of episodic memory. Further hindering progress are large conceptual differences regarding episodic memory across different fields, such as neuroscience, philosophy, and psychology. This interdisciplinary workshop therefore aims to bring together researchers from all relevant fields to advance the state of the art in the research on generative episodic memory. FOR 2812 ?Constructing scenarios of the past: A new framework in episodic memory? consists of 9 researchers. Seven from the Ruhr University Bochum and two from the University of M?nster. The consortium adopts an interdisciplinary approach and investigates generative episodic memory from a conceptual, modeling, and experimental perspective using a common conceptual framework: scenario construction. Paper submission deadlines [GMT +1 (CET)]: Abstract submission - 15.11.2020 Notification of acceptance - 19.12.2020 Submission guidelines: Abstracts must be submitted in English and be no longer than 1 page. Submitted work must be original and unpublished. Abstracts must be submitted electronically through the GEM 2021 paper submission site on EasyChair https://easychair.org/cfp/gem2021 . Authors will receive confirmation of receipt of their abstracts including an ID number after submission. You can edit your submission at any time before the deadline. We will consider only the final version. Program committee: Nikolai Axmacher - Faculty of Psychology - Ruhr University Bochum Sen Cheng - Institute for Neural Computation - Ruhr University Bochum Gerald Echterhoff - Faculty of Psychology - University of M?nster Albert Newen - Faculty of Philosophy - Ruhr University Bochum Ricarda Schubotz - Faculty of Psychology - University of M?nster Markus Werning - Faculty of Philosophy - Ruhr University Bochum Laurenz Wiskott - Institute for Neural Computation - Ruhr University Bochum Oliver Wolf - Faculty of Psychology - Ruhr University Bochum All questions regarding the workshop should be emailed to for2812 at rub.de Coordinator - Vinita Samarasinghe Secretary - Christiane Dahl -- Vinita Samarasinghe M.Sc., M.A. Science Manager Arbeitsgruppe Computational Neuroscience Institut f?r Neuroinformatik Ruhr-Universit?t Bochum, NB 3/26 Postfachnummer 110 Universit?tstr. 150 44801 Bochum Tel: +49 (0) 234 32 27996 Email: samarasinghe at ini.rub.de -------------- next part -------------- An HTML attachment was scrubbed... URL: From aapo.hyvarinen at helsinki.fi Mon Oct 5 04:32:39 2020 From: aapo.hyvarinen at helsinki.fi (=?UTF-8?Q?Aapo_Hyv=c3=a4rinen?=) Date: Mon, 5 Oct 2020 11:32:39 +0300 Subject: Connectionists: Postdoc in Unsupervised Deep Learning, U Helsinki Message-ID: Applications are invited for a postdoctoral position in *** Unsupervised Deep Learning *** in a project lead by Aapo Hyvarinen at the University of Helsinki. The project is broadly defined, and includes cutting-edge frameworks such as nonlinear ICA, energy-based modelling, and causal discovery. Examples of our recent work include: https://arxiv.org/abs/1907.04809 https://arxiv.org/abs/2002.11537 https://arxiv.org/abs/1904.09096 However, the scope of the project is flexible and depends on the interests of the candidate. The project may also involve a strong component of analysing data from brain imaging experiments (fMRI, EEG or MEG). The post-doc is part of the new European-wide ELLIS framework, of which Helsinki is one site. Applications from candidates with a PhD degree in computer science, statistics, or similar, are welcome. Candidates who are likely to obtain a PhD degree in the next few months can also apply. The starting date and the duration are flexible. For more details, see https://www.helsinki.fi/en/open-positions/postdoctoral-researcher-in-unsupervised-deep-learning Aapo Hyvarinen From somidshafiei at google.com Mon Oct 5 05:16:09 2020 From: somidshafiei at google.com (Shayegan Omidshafiei) Date: Mon, 5 Oct 2020 11:16:09 +0200 Subject: Connectionists: Call for papers: AAAI Spring Symposium on Challenges and Opportunities for Multi-Agent Reinforcement Learning (COMARL) 2021 Message-ID: AAAI Spring Symposium on Challenges and Opportunities for Multi-Agent Reinforcement Learning (COMARL) 2021 March 22-24, 2021, Stanford University in Palo Alto, California, USA. https://sites.google.com/corp/view/comarl-aaai-2021/call-for-papers Key Dates: Submission: November 1st, 2020, 23:59 GMT Notification: December 3rd, 2020 Symposium: March 22?24, 2021 Call for position papers to define a topic of study at the symposium: We live in a multi-agent world and to be successful in that world intelligent agents will need to learn to take into account the agency of others. They will need to compete in market places, cooperate in teams, communicate with others, coordinate their plans, and negotiate outcomes. Examples include self-driving cars interacting in traffic, personal assistants acting on behalf of humans and negotiating with other agents, swarms of unmanned aerial vehicles, financial trading systems, robotic teams, and household robots. There has been a lot of great work on multi-agent reinforcement learning (MARL) in the past decade, but significant challenges remain, including: - the difficulty of learning an optimal model/policy from a partial signal, - learning to cooperate/compete in non-stationary environments with - distributed, simultaneously learning agents, - the interplay between abstraction and influence of other agents, - the exploration vs. exploitation dilemma, - the scalability and effectiveness of learning algorithms, - avoiding social dilemmas, and - learning emergent communication. The purpose of this symposium is to bring together researchers in multiagent reinforcement learning, but also more widely machine learning and multiagent systems, to explore some of these and other challenges in more detail. The main goal is to broaden the scope of MARL research and to address the fundamental issues that hinder the applicability of MARL for solving complex real world problems. We aim to organize an active workshop, with many interactive (brainstorm/breakout) sessions. We are hopeful that this will form the basis for ongoing collaborations on these challenges between the attendants and we aim for several position papers as concrete outcomes. Authors can submit papers of 1-4 pages that will be reviewed by the organizing committee. We are looking for position papers that present a challenge or opportunity for MARL research, which should be on a topic the authors not only wish to interact on but also ?work? on with other participants during the symposium. We also welcome (preliminary) research papers that describe new perspectives to dealing with MARL challenges, but we are not looking for summaries of current research---papers should clearly state some limitation(s) of current methods and potential ways these could be overcome. Submissions will be handled through easychair: https://easychair.org/conferences/?conf=sss21 ----------------------------------------------------------------------------------------------------------------- Special note for authors of papers accepted to last year?s COMARL 2020 symposium As communicated earlier, we are pleased to announce that all of the papers previously accepted to COMARL 2020 (postponed due to COVID-19) will, of course, naturally be presented at COMARL 2021. Moreover, given the time lapsed since the 2020 session, we would like to offer authors who had their papers accepted for the March 2020 session the following options for the 2021 session: 1. Presenting their 2020 paper as-is in the new session. 2. Submitting a minor revision of their paper (i.e., minor updates/improvements, and no major change in topic). The organizing committee will subsequently verify the changes are minor (i.e., a minimal review). 3. Conduct a major revision of their 2020 paper. This will involve a full review by the PC. 4. Submitting a new paper altogether (and choosing to also present their 2020 paper as-is). This will involve a full review by the PC. The deadline for submissions of minor, major, and new papers (Options 2-4 above) is November 1st, 2020, 23:59 GMT, with submissions made on https://easychair.org/conferences/?conf=sss21. Please let us know your preferences as soon as possible. ----------------------------------------------------------------------------------------------------------------- Best regards, Organizing Committee: Christopher Amato, Northeastern University Frans Oliehoek, Delft University of Technology Shayegan Omidshafiei, Google DeepMind Karl Tuyls, Google DeepMind -------------- next part -------------- An HTML attachment was scrubbed... URL: From pablo.alvesdebarros at iit.it Mon Oct 5 08:51:38 2020 From: pablo.alvesdebarros at iit.it (Pablo Vinicius Alves De Barros) Date: Mon, 5 Oct 2020 12:51:38 +0000 Subject: Connectionists: Call For Abstracts - Workshop on Affective Shared Perception (WASP) Message-ID: Dear all, We are delighted to invite you to submit an abstract, and to participate in our Workshop on Affective Shared Perception (WASP), hosted by the International Conference on Developmental Learning and Epigenetic Robotics (ICDL-EPIROB2020). Please find below all the information! Cheers, Pablo I. Aim and Scope Our perception of the world, in particular, the ones which are influenced by affective understanding, depends both on sensory perception and prior knowledge. Most of the current research on modeling affective behavior as computer models ground their contribution to pre-trained learning models, which are purely data-driven, or on reproducing existing human behavior. Such approaches allow for easily reproducible solutions that fail when applied to complex social scenarios. Understanding shared perception as part of the affective processing mechanisms will allow us to tackle this problem and to provide the next step towards a real-world affective computing system. The goal of this workshop is to present and discuss new findings, theories, systems, and trends in computational models of affective shared perception. The workshop will feature a multidisciplinary list of invited speakers with experience in different aspects of social interaction, which will allow a rich and diverse debate about our overarching theme of affective shared perception. The workshop is scheduled to happen on the 30th of October of 2020 virtually. It will start at 15h00 CET and it will have a total duration of 3h30min. The participation is free, and a Zoom room will be available shortly before the workshop starts. II. Registration The registration to the workshop is free, but to guarantee a place to attend the workshop, please register here: https://forms.office.com/Pages/ResponsePage.aspx?id=XkYvv3Ufb0u-Kb9TJzvB2u5KiGG9gI9Jl0u_PdkIVS5UODk0UE43V1VJQVgxQVlJWVo0R1g0WUxQMi4u III. Potential Topics Topics include, but are not limited to: - Affective perception and learning - Affective modulation and decision making - Developmental perspectives of shared perception - Machine learning for shared perception - Bio-inspired approaches for affective shared perception - Affective processing for embodied and cognitive robots - Multisensory modeling for conflict resolution in shared perception - New psychological findings on shared perception - Assistive aspects and applications of shared affective perception IV. Invited Speakers Prof. Dr. Ginevra Castellano - Uppsala University, Sweeden Prof. Dr. Ellen Souza - Federal Rural University of Pernambuco, Brazil Prof. Dr. Yukie Nagai - The University of Tokyo, Japan V. Submission Prospective participants in the workshop are invited to submit a contribution as an abstract with a maximum of 350 words. Submission information: https://www.whisperproject.eu/wasp2020 The abstracts will be peer-reviewed by experts from all over the world. To encourage the integration with the local affective computing communities, we will allow student abstracts to be submitted in English, Spanish, and Portuguese. Each accepted abstract will be presented as a 5 min video (in English!) that will be shared on the workshop's social media. During the workshop, all the videos will be streamed and the authors will have a joint live Q/A with the audience for 60minutes. Participants can also opt-in for participating in our Frontiers Research Topic on Affective Shared Perception ( https://www.frontiersin.org/research-topics/16086/affective-shared-perception). The same abstract sent to the workshop can be sent as an abstract submission to the research topic. If you want to opt-in for the research topic, only English submissions will be accepted. - Abstract submission deadline: 12th of October - Notification of acceptance: 17th of October - Frontiers Research Topic Abstract Deadline: 24th of October - Video submission: 24th of October VI. Organizers Pablo Vinicius Alves De Barros, Italian Institute of Technology (IIT), Genova, Italy Alessandra Sciutti, Italian Institute of Technology (IIT), Genova, Italy VII. Acknowledgment The workshop is organized in the framework of the Starting Grant wHiSPER (G.A. No 804388) funded by the European Research Council (ERC) under the European Union?s Horizon 2020 research and innovation programme. ---------------------------------------- Dr. Pablo Barros Postdoctoral Researcher - CONTACT Unit Istituto Italiano di Tecnologia ? Center for Human Technologies Via Enrico Melen 83, Building B 16152 Genova, Italy email: pablo.alvesdebarros at iit.it website: https://www.pablobarros.net twitter: @PBarros_br -------------- next part -------------- An HTML attachment was scrubbed... URL: From terry at salk.edu Mon Oct 5 13:22:56 2020 From: terry at salk.edu (Terry Sejnowski) Date: Mon, 05 Oct 2020 10:22:56 -0700 Subject: Connectionists: NEURAL COMPUTATION - October 1, 2020 In-Reply-To: Message-ID: Neural Computation - Volume 32, Number 10 - October 1, 2020 available online for download now: http://www.mitpressjournals.org/toc/neco/32/10 http://cognet.mit.edu/content/neural-computation ----- Article Fast and Accurate Langevin Simulations of Stochastic Hodgkin-Huxley Dynamics Shusen Pu, Peter J. Thomas Letters A Predictive-Coding Network That Is Both Discriminative and Generative Wei Sun, Jeff Orchard Binless Kernel Machine: Modeling Spike Train Transformation for Cognitive Neural Prostheses Cunle Qian, Xuyun Sun, Yueming Wang, Xiaoxiang Zheng, Yiwen Wang, and Gang Pan Modal Principal Component Analysis Keishi Sando, Hideitsu Hino Multi-view Alignment and Generation in CCA via Consistent Latent Encoding Yaxin Shi, Yuangang Pan, Donna Xu, and Ivor W. Tsang Analysis of Regression Algorithms With Unbounded Sampling Hongzhi Tong, Jiajing Gao Active Learning of Bayesian Linear Models With High-Dimensional Binary Features by Parameter Confidence-Region Estimation Yu Inatsu, Masayuki Karasuyama, Keiichi Inoue, Hideki Kandori, and Ichiro Takeuchi Active Learning for Enumerating Local Minima Based on Gaussian Process Derivatives Yu Inatsu, Daisuke Sugita, Kazuaki Toyoura, and Ichiro Takeuchi ------------ ON-LINE -- http://www.mitpressjournals.org/neuralcomp MIT Press Journals, One Rogers Street, Cambridge, MA 02142-1209 Tel: (617) 253-2889 FAX: (617) 577-1545 journals-cs at mit.edu ------------ From georg.martius at tuebingen.mpg.de Tue Oct 6 06:45:00 2020 From: georg.martius at tuebingen.mpg.de (Georg Martius) Date: Tue, 6 Oct 2020 12:45:00 +0200 Subject: Connectionists: =?utf-8?q?Call_for_Papers_-_NeurIPS_2020_Workshop?= =?utf-8?q?_=E2=80=9CLearning_Meets_Combinatorial_Optimization=E2=80=9D_?= =?utf-8?b?KExNQ0Ep?= Message-ID: Dear colleagues, Please consider submitting to the NeurIPS 2020 Workshop ?Learning Meets Combinatorial Optimization? (LMCA). The new extended deadline is Oct 16, 2020 (11:59PM UTC). We are soliciting 4-page extended abstract submissions. Full submission instructions can be found on the workshop website: https://sites.google.com/view/lmca2020 along with the list of invited speakers. Why this workshop? Machine learning algorithms have been shown to generalize poorly on combinatorially demanding tasks. Recent research has demonstrated that merging combinatorial optimization with machine learning methods enables solving problems that require non-trivial combinatorial generalization beyond pattern matching. In this spirit, this workshop aims to bring the communities (machine learning and combinatorial optimization, operations research) together in order to motivate further research at the intersection. This involves: * Machine learning approaches aimed at improving combinatorial algorithms/solvers. * Machine learning techniques to directly learn solvers for combinatorial problems. * Hybrid architectures; pipelines containing both algorithmic/combinatorial and standard NN building blocks. * Applications of the above. We are looking forward to some great contributions. Kind regards from the organization team, Marin Vlastelica, Jialin Song, Aaron Ferber, Brandon Amos, Georg Martius, Bistra Dilkina, Yisong Yue From eilif.muller at umontreal.ca Tue Oct 6 10:32:03 2020 From: eilif.muller at umontreal.ca (Muller Eilif) Date: Tue, 6 Oct 2020 14:32:03 +0000 Subject: Connectionists: PhD/post-doc opening on Neuro-AI / Dendritic Algorithms for Perceptual Learning in Montreal, Canada Message-ID: I'm happy to announce the Architectures of Biological Learning Lab is Hiring! I'm looking for exceptional candidates at the MSc, PhD or post-doc level to work on "Dendritic Algorithms for Perceptual Learning". The project will employ simulations of pyramidal neurons and plasticity, and deep convolutional networks to study representation learning in the neocortex. Prior experience with Python, NEURON, and/or PyTorch would be an asset. This project will be undertaken in collaboration with Profs. Yoshua Bengio (UdeM, Mila), Roberto Araya (UdeM, CRCHUSJ), and Blake Richards (McGill, Mila). Montreal, Canada is a thriving international hub for Artificial Intelligence and Neuroscience research, with a booming AI industry. It's where Donald O. Hebb originally formulated Hebbian Learning. It's also a vibrant, funky, cosmopolitan yet affordable city of over 4 million, referred to as "Canada's Cultural Capital" by Monocle magazine. In 2017, Montreal was ranked the 12th-most liveable city in the world by the Economist Intelligence Unit in its annual Global Liveability Ranking, and the best city in the world to be a university student in the QS World University Rankings. For more details and instructions how to apply, please visit: https://bit.ly/3l1PGFH --- Eilif B. Muller, Ph.D. IVADO Assistant Research Professor Department of Neurosciences, Faculty of Medicine, University of Montreal Associate Faculty Member - Quebec Artificial Intelligence Institute (Mila) Centre de recherche du CHU Sainte-Justine 3175 C?te Sainte-Catherine, Montr?al QC H3T 1C5, Canada -------------- next part -------------- An HTML attachment was scrubbed... URL: From keller at inf.ed.ac.uk Tue Oct 6 17:07:02 2020 From: keller at inf.ed.ac.uk (Frank Keller) Date: Tue, 6 Oct 2020 22:07:02 +0100 Subject: Connectionists: Four year PhD studentships in NLP at Edinburgh Message-ID: <24444.56438.998941.746470@bruegel.inf.ed.ac.uk> FULLY FUNDED FOUR-YEAR PHD STUDENTSHIPS UKRI CENTRE FOR DOCTORAL TRAINING IN NATURAL LANGUAGE PROCESSING Based at the University of Edinburgh: in conjunction with School of Informatics and School of Philosophy, Psychology and Language Sciences. Deadlines: v Non UK : 27^th November 2020 v UK : 29^th January 2021 Applications are now sought for the CDTs third Cohort of students to start in September 2021. * * * The CDT in NLP offers unique, tailored doctoral training comprising both taught courses and a doctoral dissertation over four years. Each student will take a set of courses designed to complement their existing expertise and give them an interdisciplinary perspective on NLP. The studentships are fully funded for the four years and come with a generous allowance for travel, equipment and research costs. The CDT brings together researchers in NLP, speech, linguistics, cognitive science and design informatics from across the University of Edinburgh. Students will be supervised by a world-class faculty of over 60 supervisors and will benefit from cutting edge computing and experimental facilities, including a large GPU cluster and eye-tracking, speech, virtual reality and visualisation labs. The CDT involves a number of industrial partners, including Amazon, Facebook, Huawei, Microsoft, Naver, Toshiba, and the BBC. Links also exist with the Alan Turing Institute and the Bayes Centre. A wide range of research topics fall within the remit of the CDT: w Natural language processing and computational linguistics w Speech technology w Dialogue, multimodal interaction, language and vision w Information retrieval and visualization, computational social science w Computational models of human cognition and behaviour, including language and speech processing w Human-Computer interaction, design informatics, assistive and educational technology w Psycholinguistics, language acquisition, language evolution, language variation and change w Linguistic foundations of language and speech processing. The next cohort of CDT students will start in September 2021 and is now open for applications. Around 12 studentships are available, covering maintenance at the research council rate^ (currently GBP 15,285 per year) plus tuition fees. Studentships are open to all nationalities and we are particularly keen to receive applications from women, minority groups and members of other groups that are underrepresented in technology. Applicants in possession of other funding scholarships or industry funding are also welcome to apply - please provide details of your funding source on your application. Applicants should have an undergraduate or master's degree in computer science, linguistics, cognitive science, AI, or a related discipline; or have a breadth of relevant experience in industry/academia/public sector, etc. Further details, including the application procedure, can be found at: [2]http://nlp-cdt.ac.uk/ Application Deadlines Early application is encouraged but completed applications must be received at the latest by: 27^th November 2020 (non UK applicants) or 29th January 2021 (UK applicants). CDT in NLP Open Day Find out more about the programme by attending the PG Virtual Open Week 9-13^ November when the CDT in NLP will be hosting an event - date/time to be advised. Click [3]here to join mailing list. Enquiries Please direct any enquiries to the CDT admissions team at: [4]cdt-nlp-info at inf.ed.ac.uk. ^ [5]https://www.ukri.org/skills/funding-for-research-training/ Sally Galloway UKRI CDT in Natural Language Processing - Coordinator [6]UKRI CDT in NLP School of Informatics, University of Edinburgh, Informatics Forum, 10 Crichton St, Edinburgh EH8 9AB Email: [7]cdt-nlp-info at inf.ed.ac.uk Tel: +44 (0) 131 650 3130 References 1. https://twitter.com/Edin_CDT_NLP/status/1313132927014895619 2. http://nlp-cdt.ac.uk/ 3. https://www.ed.ac.uk/studying/postgraduate/open-days-events-visits/open-days/postgraduate-virtual-open-days 4. mailto:cdt-nlp-info at inf.ed.ac.uk 5. https://www.ukri.org/skills/funding-for-research-training/ 6. http://nlp-cdt.ac.uk/ 7. mailto:cdt-nlp-info at inf.ed.ac.uk -- The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336. From keller at inf.ed.ac.uk Tue Oct 6 17:07:43 2020 From: keller at inf.ed.ac.uk (Frank Keller) Date: Tue, 6 Oct 2020 22:07:43 +0100 Subject: Connectionists: PhD studentships in Computational Linguistics, Speech Technology and Cognitive Science, Edinburgh Message-ID: <24444.56479.742565.613657@bruegel.inf.ed.ac.uk> PHD STUDENTSHIPS IN COMPUTATIONAL LINGUISTICS, SPEECH TECHNOLOGY AND COGNITIVE SCIENCE Institute for Language, Cognition and Computation School of Informatics University of Edinburgh The Institute for Language, Cognition and Computation (ILCC) at the University of Edinburgh invites applications for three-year PhD studentships starting in September 2021. ILCC is dedicated to the pursuit of basic and applied research on computational approaches to language, communication and cognition. Primary research areas include: * Natural language processing and computational linguistics * Machine Translation * Speech technology * Dialogue, multimodal interaction, language and vision * Computational Cognitive Science , including language and speech, decision-making, learning and generalization * Social Media and Computational Social Science * Human-Computer interaction, design informatics, assistive and educational technology * Information retrieval and visualization Approximately 10 studentships from a variety of sources are available, covering both maintenance at the research council rate of GBP 15,285 per year and tuition fees. Studentships are available for UK, EU, and non-EU nationals. Applicants should have a strong undergradudate degree or equivalent in computer science, cognitive science, AI, or a related discipline. For a list of academic staff at ILCC with research areas, and for a list of indicative PhD topics, please consult: http://web.inf.ed.ac.uk/ilcc/people/academic-senior-research-staff http://www.ilcc.inf.ed.ac.uk/study/possible-phd-topics-in-ilcc Details regarding the PhD programme and the application procedure can be found at: http://www.ed.ac.uk/informatics/postgraduate/research-degrees/phd There are TWO DEADLINES for applications to receive full consideration: round 1: 27th November 2020 round 2: 29th January 2021 We strongly recommend that non-UK applicants submit their applications in round 1, to maximise their chances of funding. Please direct inquiries to the PhD admissions team at ilcc-admissions at inf.ed.ac.uk. Please note that the 3-year ILCC PhD program is distinct from the UKRI Centre for Doctoral Training in Natural Language Processing, which offers a 4-year PhD with integrated study: http://nlp-cdt.ac.uk/ -- The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336. From jonas.n.myhre at uit.no Wed Oct 7 09:27:39 2020 From: jonas.n.myhre at uit.no (Jonas Nordhaug Myhre) Date: Wed, 7 Oct 2020 13:27:39 +0000 Subject: Connectionists: Call for papers: the 4th Northern Lights Deep Learning Workshop, 18-20 January 2021 Message-ID: *** Apologies for cross-posting *** Following the success of previous years, we are organizing the 4th Northern Lights Deep Learning Workshop on 18-20 January 2021. Like the past years, it will be an informal workshop on deep learning theory and applications in Troms?, Norway*. Please see http://www.nldl.org for more information. We are happy to have top international keynote speakers, including * Lars Kai Hansen, Department of Applied Mathematics and Computer Science ? DTU Compute * Laura Leal-Taixe, Dynamic Vision and Learning Group - The Technical University of M?nich. * Arthur Gretton, Centre for Computational Statistics and Machine Learning (CSML) at University College London. * Elsa D. Angelini, Imperial Biomedical Research Centre - National Institute of Healthcare Research (UK). * Roland Vollgraf, Zalando Research This year, we are accepting two alternatives for contributions: (1) Full paper submissions (6 pages) will be presented either as orals or as posters and made published in the conference proceedings after the workshop; (2) Extended abstracts (2 pages) will be presented either as orals or as posters (but not published in the conference proceedings). Deadline for both types of submissions: 9th November 2020. Instructions on template etc. can be found on http://www.nldl.org. Further, we will be holding a mini deep learning school (smaller tutorials). More info will be made available on https://www.nldl.org/program. * Due to the COVID-19 situation, the workshop will be held virtually. Kind regards, The NLDL 2021 Organizing committee -------------- next part -------------- An HTML attachment was scrubbed... URL: From jenny.benois-pineau at u-bordeaux.fr Wed Oct 7 09:15:37 2020 From: jenny.benois-pineau at u-bordeaux.fr (jbenoisp) Date: Wed, 7 Oct 2020 15:15:37 +0200 Subject: Connectionists: ICPR2020 WS EDL/AI The dead-line is EXTENDED October 17th! Message-ID: <6A9F0E7C-7368-4E1B-B4FF-9CF6B62DA40E@u-bordeaux.fr> ----------------We apologize if you receive this message several times--------- Call for papers ICPR?2020 Workshop. WS GOES ONLINE. THE SUBMISSION DEAD-LINE IS Extended October 17! **************************Explainable Deep Learning/AI******************** https://edl-ai-icpr.labri.fr/ Date: January 11th 2021 THE SUBMISSION DEADLINE IS EXTENDED OCTOBER 17th The recent focus of AI and Pattern Recognition communities on the supervised learning approaches, and particularly to Deep Learning / AI, resulted in considerable increase of performance of Pattern Recognition and AI systems, but also raised the question of the trustfulness and explainability of their predictions for decision-making. Instead of developing and using Deep NNs as black boxes and adapting known architectures to variety of problems, the goal of explainable Deep Learning / AI is to propose methods to ?understand? and ?explain? how the these systems produce their decisions. The goals of the workshop are to bring together research community which is working on the question of improving explainability of AI and Pattern Recognition algorithms and systems. The topics of the workshop cover but are not limited to: ? ?Sensing? or ?salient features? of Neural Networks and AI systems - explanation of which features for a given configuration yield predictions both in spatial (images) and temporal (time-series, video) data; ? Attention mechanisms in Deep Neural Networks and their explanation; ? For temporal data, the explanation of which features and at what time are the most prominent for the prediction and what are the time intervals when the contribution of each data is important; ? How the explanation can help on making Deep learning architectures more sparse (pruning) and light-weight; ? When using multimodal data how the prediction in data streams are correlated and explain each other; ? Automatic generation of explanations / justifications of algorithms and systems? decisions; ? Decisional uncertainly and explicability ? Evaluation of the explanations generated by Deep Learning and other AI systems. *** Pannel: ?Toward more explainable Deep Learning and AI systems?, Chair: Dragutin Petcovic(SFSU,USA) Moderator will ask invited speakers to briefly present their opinions and ideas on the topic of the panel and then the audience will be invited to a discussion *** Important Dates: Submission deadline EXTENDED (Hard deadline): October 17th 2020 Workshop author notification: November 10th 2020 Camera-ready submission: November 15th 2020 Finalized workshop program: December 1st 2020 *** Paper Submission: The Proceedings of the EDL-AI 2020 workshop will be published in the Springer Lecture Notes in Computer Science (LNCS) series. Papers will be selected by a single blind (reviewers are anonymous) review process. Submissions must be formatted in accordance with the Springer's Computer Science Proceedings guidelines. Two types of contribution will be considered: Full paper (12-15 pages) Short papers (6-8 pages) *** Submission site: is Open https://edl-ai-icpr.labri.fr Program Committee: Christophe Garcia (LIRIS, France) Hugues Talbot (EC, France) Dragutin Petkovic (SFSU,USA) Alexandre Beno?t( LISTIC,France) Mark T. Keane (UCD, Ireland) Georges Quenot(LIG, France) Stefanos Kolias (NTUA, Grece) Jenny Benois-Pineau(LABRI, France) Herv? Le Borgne (LIST, France) Noel O?Connor (DCU, Ireland) Nicolas Thome(CNAM, France) Due to COVID situation, the WorkShop Will be in ONLINE "live" Format. ALL ACCEPTED PAPERS WILL BE PUBLISHED. Jenny Benois-Pineau, Georges Quenot Workshop Organizers Jenny Benois-Pineau, Professeure en Informatique, Charg?e de mission aux relations Internationales Coll?ge Sciences et Technologies, Universit? de Bordeaux 351, crs de la Lib?ration 33405 Talence France tel.: +33 (0) 5 40 00 84 24 Jenny Benois-Pineau, PhD, HDR, Professor of Computer Science, Chair of International relations School of Sciences and Technologies University of Bordeaux 351, crs de la Lib?ration 33405 Talence tel.: +33 (0) 5 40 00 84 24 -------------- next part -------------- An HTML attachment was scrubbed... URL: From amanda.louise.jacob at emory.edu Wed Oct 7 13:17:02 2020 From: amanda.louise.jacob at emory.edu (Jacob, Amanda L.) Date: Wed, 7 Oct 2020 17:17:02 +0000 Subject: Connectionists: Registration open for the Simons-Emory Workshop on Neural Dynamics Message-ID: Dear all, Registration is now open for the Simons-Emory Workshop on Neural Dynamics, which will livestream on Friday, December 4th from 11am-2pm EST. Please go here to register [1] "What could neural dynamics have to say about neural computation, and do we know how to listen?" Speakers will deliver focused 10-minute talks, with periods reserved for broader discussion on topics at the intersection of neural dynamics and computation. The website for the event is here [2] Organizer and Moderator: Chethan Pandarinath - ( Emory University and Georgia Tech ) Speakers & Discussants: Adrienne Fairhall - U Washington Mehrdad Jazayeri - MIT John Krakauer - John Hopkins Francesca Mastrogiuseppe - Gatsby / UCL Abigail Person - U Colorado Abigail Russo - Princeton Krishna Shenoy - Stanford Saurabh Vyas - Columbia We look forward to your participation! Chethan Pandarinath Investigator, Simons-Emory International Consortium on Motor Control Wallace H. Coulter Department of Biomedical Engineering Department of Neurosurgery Emory Neuromodulation and Technology Innovation Center (ENTICe) Emory University and Georgia Tech Amanda L Jacob Operations Manager, Simons-Emory International Consortium on Motor Control [1] https://docs.google.com/forms/d/1tORYWTXOdOR0p472633X_9jJp4VR169-PgglmfTv7uU/viewform?edit_requested=true [2] https://www.internationalmotorcontrol.org/dynamicsworkshop.html ________________________________ This e-mail message (including any attachments) is for the sole use of the intended recipient(s) and may contain confidential and privileged information. If the reader of this message is not the intended recipient, you are hereby notified that any dissemination, distribution or copying of this message (including any attachments) is strictly prohibited. If you have received this message in error, please contact the sender by reply e-mail message and destroy all copies of the original message (including attachments). -------------- next part -------------- An HTML attachment was scrubbed... URL: From stefano.panzeri at gmail.com Thu Oct 8 01:51:38 2020 From: stefano.panzeri at gmail.com (Stefano Panzeri) Date: Thu, 8 Oct 2020 07:51:38 +0200 Subject: Connectionists: Postdoctoral position in Computational Neuroscience, Italian Institute of Technology Message-ID: A postdoctoral position in computational neuroscience is available at Istituto Italiano di Tecnologia in Italy to work with Stefano Panzeri ( https://www.iit.it/people/stefano-panzeri). The successful candidate will conduct research in the laboratory of Neural Computation of Prof. Panzeri and in collaboration with Prof. Christopher Harvey at Harvard Medical School. We investigate, by developing and using advanced data analysis methods and neural network models, how circuits of neurons in the brain encode information and use it to produce appropriate behaviors. The Neural Computation laboratory offers a wide range of interdisciplinary expertise in computational neuroscience, including both advanced neural analysis techniques and neural network modeling. The laboratory also offers a thriving, ambitious research environment which is well funded (including several grants from the NIH Brain Initiative). This gives successful candidates ample opportunities for advanced training and personal scientific growth. We seek candidates holding a PhD in a numerate or neuroscientific discipline, with a solid computational background and a keen interest in neuroscience. They must be highly motivated and creative individuals who want to work in a dynamic, multi-disciplinary research environment and be willing to interact with both experimental and theoretical neuroscientists. For recent publications relevant to this project, see: Runyan C. A., et al (2017) Distinct timescales of population coding across cortex, *Nature*: 548: 92-96. G. Pica, et al (2017) Quantifying how much sensory information in a neural code is relevant for behavior, *Neural Information Processing Systems (NIPS 2017)* Panzeri S., et al (2017) Cracking the neural code for sensory perception by combining statistics, intervention and behaviour. *Neuron* 93: 491-507 Chettih and Harvey (2019) Single-neuron perturbations reveal feature-specific competition in V1. *Nature* 567, 334 Chong, E. et al (2020) Manipulating synthetic optogenetic odors reveals the coding logic of olfactory perception. *Science* 368, 1329. The deadline for applications is *Oct. 27th, 2020*. Applications will be examined as soon as they are received and until the position is filled. Interested applicants are strongly encouraged to email Stefano Panzeri ( stefano.panzeri at iit.it) as soon as possible, to informally inform him of their interest for the position and initiate a discussion about research projects. Formal applications should be submitted, before the deadline, through the following web site: https://iit.taleo.net/careersection/ex/jobdetail.ftl?lang=en&job=20000039 Thanks Stefano Panzeri -------------- next part -------------- An HTML attachment was scrubbed... URL: From sepand.haghighi at yahoo.com Wed Oct 7 15:17:07 2020 From: sepand.haghighi at yahoo.com (Sepand Haghighi) Date: Wed, 7 Oct 2020 19:17:07 +0000 (UTC) Subject: Connectionists: PyRGG 0.9 released: New Random Graph Generator References: <1912444518.213871.1602098227682.ref@mail.yahoo.com> Message-ID: <1912444518.213871.1602098227682@mail.yahoo.com> https://github.com/sepandhaghighi/pyrgg https://pyrgg.ir - GEXF format added?#49 - Float weight support added?#50 - tox.ini?added - Menu optimized?#48 - pyrgg.py?renamed to?graph_gen.py - Other functions moved to?functions.py - Test system modified - params.py?refactored - graph_gen.py?refactored?#63 - functions.py?refactored - weight_str_to_number?function renamed to?convert_str_to_number - branch_gen?function bugs fixed?#63 - input_filter?function bug fixed?#59 - gl_maker?function bug fixed?#67 - CONTRIBUTING.md?updated - AUTHORS.md?updated - print_test?function removed - left_justify?function removed - justify?function removed - zero_insert?function removed Best RegardsSepand Haghighi -------------- next part -------------- An HTML attachment was scrubbed... URL: From georg.martius at tuebingen.mpg.de Thu Oct 8 09:08:14 2020 From: georg.martius at tuebingen.mpg.de (Georg Martius) Date: Thu, 8 Oct 2020 15:08:14 +0200 Subject: Connectionists: Funded Ph.D. Positions at the International Max Planck Research School for Intelligent Systems - apply until November 2nd, 2020 Message-ID: <40bc62db-2c5d-fa6b-e37c-640036ee98c0@tuebingen.mpg.de> The Max Planck Institute for Intelligent Systems and the Universities of Stuttgart and T?bingen collaborate to offer an interdisciplinary Ph.D. program, the International Max Planck Research School for Intelligent Systems (IMPRS-IS). This doctoral program will accept its fifth generation of Ph.D. students in spring of 2021. This school is a key element of Baden-W?rttemberg?s Cyber Valley initiative to accelerate basic research and commercial development in artificial intelligence. We seek students who want to earn a doctorate while contributing to world-leading research in areas such as: ? Computational Cognitive Science ? Computer Graphics ? Computer Vision ? Control Systems ? Haptics ? Human-Computer Interaction ? Machine Learning ? Micro- and Nano-Robotics ? Perceptual Inference ? Robotics The participating faculty are Aamir Ahmad, Zeynep Akata, Frank Allg?wer, Alexander Badri-Spr?witz, Philipp Berens, Matthias Bethge, Michael J. Black, Andr?s Bruhn, Andreas Bulling, Martin Butz, Caterina De Bacco, Christian Ebenbauer, Peer Fischer, Andreas Geiger, Martin A. Giese, Matthias Hein, Philipp Hennig, Ardian Jusufi, Christoph Keplinger, Katherine J. Kuchenbecker, Hendrik Lensch, Falk Lieder, Jakob Macke, Georg Martius, Tian Qiu, C. David Remy, Syn Schmitt, Bernhard Sch?lkopf, Gabriele Schweikert, Michael Sedlmair, Fabian Sinz, Metin Sitti, Steffen Staab, Ingo Steinwart, J?rg St?ckler, Ulrike von Luxburg, and Felix Wichmann. Participating associated faculty include R. Harald Baayen, Wieland Brendel, Peter Dayan, Alexander Ecker, Jonathan Fiene, Bedartha Goswami, Daniel H?ufle, Anna Levina, Jim Mainprice, Kay Nieselt, Mijung Park, Nico Pfeifer, Peter Pott, Gunther Richter, Ludovic Righetti, Marc Toussaint, Sebastian Trimpe, Isabel Valera, Maria Wirzberger, and Li Zhaoping. Intelligent systems that can successfully perceive, act, and learn in complex environments hold great potential for aiding society. We seek doctoral students who are curious, creative, and passionate about research to join our school and help advance human knowledge about intelligent systems. ? You may join our program starting in spring of 2021. ? You will be mentored by our internationally renowned faculty. ? You will register as a university doctoral student and conduct research. ? IMPRS-IS offers a wide variety of scientific seminars, workshops, and social activities. ? All aspects of our program are in English. ? Your doctoral degree will be conferred when you successfully complete your Ph.D. project. ? Our dedicated staff members will assist you throughout your time as a doctoral student. People with a strong academic background and a master?s degree in Engineering, Computer Science, Cognitive Science, Mathematics, Control Theory, Neuroscience, Materials Science, Physics, or related fields should apply. We seek to increase the number of women in areas where they are underrepresented, so we explicitly encourage women to apply. We are committed to employing more handicapped individuals and especially encourage them to apply. We are an equal opportunity employer and value diversity at our institutions. Admission will be competitive. If selected, you will receive funding via an employment contract, subject to the rules of the Max Planck Society and the two participating universities. You can *apply* at https://imprs.is.mpg.de/application before 11:59 p.m. (23:59) CET on *November 2, 2020*. Finalists will be invited to selection interviews that will take place virtually from January 26 to January 29, 2021. For further information, please visit http://imprs.is.mpg.de -------------- next part -------------- A non-text attachment was scrubbed... Name: signature.asc Type: application/pgp-signature Size: 195 bytes Desc: OpenPGP digital signature URL: From nk3954 at princeton.edu Thu Oct 8 09:53:49 2020 From: nk3954 at princeton.edu (Nichol W. Killian) Date: Thu, 8 Oct 2020 13:53:49 +0000 Subject: Connectionists: request to post on listserve Message-ID: We would like to request that this notice be shared on your list serve. Can you please let me know approximately when the listing will be disbursed? Thank you and if you have any follow-up questions, please feel free to contact me. An NSF-funded multi-investigator collaboration is seeking individuals to help develop a standardized format for exchanging computational models among neuroscience, cognitive science and machine learning. The project was recently funded by NSF?s Convergence Accelerator Program, and involves Princeton Neuroscience Institute; The University of Texas at Austin; University College London; Yale Computer Science Department; and Intel Labs in collaboration with members of the broader community. We seek individuals who have considerable experience in computational modeling in cognitive science, neuroscience, and/or machine learning. Preference is for individuals with a PhD in a relevant discipline (Neuroscience, Cognitive Psychology and/or Computer Science), but others with sufficient demonstrated experience will be considered. Experience in Python is necessary, and experience in one or more existing modeling environments (e.g., NEURON, The Virtual Brain, NeuroML, Emergent, Nengo, ACT-R, PyTorch and/or TensorFlow) is preferred. Involvement can be remote. Interested individuals should contact Nichol Killian (nk3954 at princeton.edu) or Edwin Clayton (ec12 at princeton.edu). Please include a brief overview of background in the specific areas (CV attachments are welcome). Nichol Killian Project Coordinator Princeton Neuroscience Institute Princeton University -------------- next part -------------- An HTML attachment was scrubbed... URL: From hocine.cherifi at gmail.com Fri Oct 9 04:09:19 2020 From: hocine.cherifi at gmail.com (Hocine Cherifi) Date: Fri, 9 Oct 2020 10:09:19 +0200 Subject: Connectionists: CALL FOR PARTICIPATION COMPLEX NETWORKS 2020 VIRTUAL Message-ID: Dear all, COMPLEX NETWORKS 2020 proceeds as an online event with the support of the local organizing committee of Madrid. The online event will leverage Zoom. The main conference will meet on December 01-03, preceded by the half-day tutorial on November 30, 2020. Each day of the technical program will start at 10:30 am CEST and conclude at 7:15 pm CEST. The keynotes are scheduled starting at 14:45 pm CEST. COMPLEX NETWORKS 2020 accepted 246 submissions. All accepted contributions are listed at the end of this message. The registration website of COMPLEX NETWORKS 2020 is now open. The early registration deadline is October 13. Please register at your earliest possibility. https://complexnetworks.org/registration/ Best regards, and looking forward to seeing you online at COMPLEX NETWORKS 2020. Rosa M. Benito, Hocine Cherifi, Esteban Moro COMPLEX NETWORKS General Chairs Authors, title *Leo Torres, Kevin Chan, Hanghang Tong and Tina Eliassi-Rad. Non-backtracking Eigenvalues: X-Centrality and Node Immunization * *Joost Jorritsma, Tim Hulshof and J?lia Komj?thy. Not all interventions are equal for the height of the second peak * *Andreia Sofia Teixeira, Szymon Talaga, Trevor James Swanson and Massimo Stella. Revealing semantic and emotional structure of suicide notes with cognitive network science * *Salvatore Vilella, Mirko Lai, Daniela Paolotti and Giancarlo Ruffo. Immigration in the Italian Public Debate: Dynamics of Interactions in a Segregated Network * *Eladio Montero-Porras, Riccardo Gallotti, Tom Lenaerts and Jelena Grujic. Networks make us more cautious: using Drift Diffusion Model to measure the learning process in Prisoner's Dilemma on different network topologies. * *Gergo Toth, Johannes Wachs, Riccardo Di Clemente, Akos Jakobi, Bence Sagvari, Janos Kertesz and Balazs Lengyel. Inequality is rising where social network segregation interacts with urban topology * *Feifan Liu, Shuang Zhang, Shuangling Luo and Haoxiang Xia. Mapping the Global Scientific Landscape of Virology Before the COVID-19 Pandemic: A Large-Scale Document Analysis with the Representation Learning and Network Visual Representation * *Weiran Cai, Belgin San-Akca, Jordan Snyder, Grayson Gordon, Zeev Maoz and Raissa D'Souza. Global Network of Hidden Military Support: its Structure and Evolution * *Philip Waggoner. Are there Racial Disparities in Fatal Police Shootings? Exploration with Uniform Manifold Approximation and Projection * *Bojan Evkoski, Igor Mozeti?, Nikola Ljube?i? and Petra Kralj Novak. Evolution of Political Polarization on Twitter * *Rion Brattig Correia, Paulo Navarro Costa and Luis M. Rocha. Extraction of overlapping modules in networks via spectral methods and information theory * *Inho Hong, Alex Rutherford, Leonardo Ferreira and Manuel Cebrian. Epidemic-driven con?ict and con?ict-driven epidemics * *Jason Bassett, Niccolo Pescetelli, Alex Rutherford and Manuel Cebrian. Time-critical Crowdsourced Responses and EmergencyMitigation to Global Biosecurity Threats * *Tobias Reisch, Georg Heiler, Jan Hurt, Peter Klimek and Stefan Thurner. Behavioral gender differences are reinforced during the COVID-19 crisis * *Tommaso Radicioni, Tiziano Squartini and Fabio Saracco. The Italian Twittersphere discussion on migration: a network analysis * *Egemen Sert, Alfredo Morales and Yaneer Bar-Yam. Segregation dynamics with reinforcement learning andagent based modeling * *Ashleigh Myall, Robert Peach, Andrea Weisse, Siddharth Mookerjee, Frances Davies, Alison Holmes and Mauricio Barahona. Revealing transmission of healthcare-associated infections using network-constrained patient trajectories * *Matthew Jackson, Suraj Malladi and David McAdams. Learning through the Grapevine: the Impact of Message Mutation, Transmission Failure, and Deliberate Bias * *Javier Garc?a-Algarra, Mary Luz Mouronte-L?pez, Javier Galeano and Gonzalo G?mez-Bengoechea. A network model of World Trade inequality and how to mitigate it * *Anton Pichler and J. Doyne Farmer. Shock propagation in supply and demand constrained input-output economies * *Kathryn Turnbull, Simon Lunagomez, Christopher Nemeth and Edoardo Airoldi. Latent Space Modelling of Hypergraph Data * *Eszter Bokanyi, S?ndor Juh?sz, M?rton Karsai and Balazs Lengyel. The effect of commuting on the structure and assortativity of online social ties * *Rory Humphries, Kieran Mulchrone and Philipp Hoevel. A Systematic Framework of Modelling Epidemics on Temporal Networks * *Aldo Acevedo, Claudio Duran, Alessandro Muscoloni and Carlo Cannistraci. Evaluating network embedding by community separability * *Alexis Arnaudon, Robert Peach and Mauricio Barahona. Learning on graphs with diffusion * *Robert Peach, Alexis Arnaudon, Henry Palasciano and Mauricio Barahona. Highly comparative graph analysis * *Weiran Cai, Jordan Snyder, Alan Hastings and Raissa D'Souza. Assembling Mutualistic Networks from Adaptive Niche Interactions * *Regina Duarte, Qiwei Han and Claudia Soares. Dissecting medical referral mechanisms in health services using graph neural networks * *Zachary Boyd, Nicolas Fraiman, Jeremy Marzuola, Peter Mucha, Braxton Osting and Jonathan Weare. A metric on directed graph nodes based on hitting probabilities * *Ricardo Guti?rrez and Carlos P?rez-Espigares. Generalized optimal paths revealed through the large deviations of random walks on networks * *Ilias Rentzeperis, Steeve Laquitaine and Cees van Leeuwen. Adaptive rewiring evolves brain-like structure in directed networks * *Marcell Nagy and Roland Molontay. Comparing Box-Covering Algorithms for Fractal Dimension of Complex Networks * *Marcell Nagy and Roland Molontay. Data-Driven Analysis of Complex Networks and Their Model-Generated Counterparts * *Arkadiusz J?drzejewski, Joanna Toruniewska, Krzysztof Suchecki, Oleg Zaikin and Janusz Ho?yst. Spontaneous symmetry breaking of active phase in coevolving nonlinear voter model * *Bianka Kov?cs and Gergely Palla. Unintended communities in hyperbolic networks * *David Mart?n-Corral, Esteban Moro and Nick Obradovich. Nowcasting country-wide headache symptoms from social media traces and air quality * *Stephany Rajeh, Marinette Savonnet, Eric Leclercq and Hocine Cherifi. Assessing the Relationship Between Centrality and Hierarchy Measures in Complex Networks * *Stefan Katz and Aleksandra Urman. Dynamic Social Media Network Analysis: an Edge Depreciation Approach * *Nicola Amoroso, Loredana Bellantuono, Saverio Pascazio, Alfonso Monaco and Roberto Bellotti. Reconstructed potentials to characterize complex networks * *Takayuki Mizuno, Shohei Doi, Takahiro Tsuchiya and Shuhei Kurizaki. Socially Responsible Investing in the Global Ownership Network and its implications for International Security * *Tomasz W?s, Talal Rahwan and Oskar Skibski. Random Walk Decay Centrality * *Erik Braun, Tibor Kiss and Tam?s Sebesty?n. Foreign lockdown in supply networks: a cross-country analysis of economic independence * *Alfonso Allen-Perkins, Mar?a Hurtado de Mendoza, David Garc?a-Callejas, Oscar Godoy and Ignasi Bartomeus. The macro-, meso- and micro-structure of individual-based community-wide plant-pollinator networks reflects pollen flow dynamics and plant reproductive success * *Naim Bro and Marcelo Mendoza. Paternal-maternal surname networks reveal the population structure of Santiago, Chile * *Nayade Garc?s and V?ctor Mu?oz. Analysis of Variable Stars via Visibility Graph Algorithm * *Amy Schweikert, Guillaume L'Her and Mark Deinert. Prioritizing investments in critical facility access during and following natural hazard events using geospatial data and network perturbation models * *Lucio La Cava, Lucas E. Ruffo and Andrea Tagarelli. Towards Mesoscopic Structural Analysis of the Fediverse of Decentralized Social Networks * *Alexander Gates, Rion Brattig Correia, Xuan Wang and Luis M. Rocha. The effective graph: a weighted graph that captures nonlinear logical redundancy in biochemical systems * *Eytan Katzav, Ido Tishby and Ofer Biham. Convergence towards an Erdos-Renyi graph structure in network contraction processes * *Lorenzo Zangari, Roberto Interdonato and Andrea Tagarelli. Graph Neural Network Models for Node Classification in Multilayer Networks * *Bel?n Acosta, Denisse Past?n and Pablo S. Moya. Horizontal Visibility Graph: Irreversibility of Turbulent and Non-Collisional Plasmas Magnetic Fluctuations * *Leonardo Gutierrez, Alexandre Bovet and Jean-Charles Delvenne. Multi-scale Anomaly Detection on Attributed Networks * *Bogumil Kaminski, Tomasz Olczak, Pawel Pralat and Fran?ois Th?berge. Sequential and parallel generation of Artificial Benchmark for Community Detection (ABCD) graphs * *Hadar Miller and Osnat Mokryn. Size agnostic change point detection framework for evolving networks * *Amin Kaveh, Matteo Magnani and Oskar Dahlin. Probabilistic Network Sparsification by Betweenness * *Daniel Feinstein and Ebrahim Patel. Max-Plus Opinion Dynamics With Temporal Confidence * *Isabel P?rez-Jover and Jacobo Aguirre. Viral Infection From a Complex Networks Perspective * *Balazs Lengyel, Eszter Bok?nyi, Riccardo Di Clemente, Janos Kertesz and Marta Gonz?lez. The role of geography in the complex diffusion of innovations * *Philipp Hoevel, Rory Humphries, Mary Spillane, Kieran Mulchrone, Sebastian Wieczorek and Micheal O'Riordain. On an all-Ireland SIRX Network Model for the Spreading of SARS-CoV-2 * *J. Leonel Rocha and S?nia Carvalho. Synchronizability and information transmission in complete dynamical networks of discontinuous maps * *Tam?s Sebesty?n and Bal?zs Szab?. Market Interaction Structure Behind Price Heterogenity in a Monopolistic Market * *Tommaso Cavalieri, Andrea Fedele, Federica Guiducci, Valentina Olivotto and Giulio Rossetti. A network analysis of personnel exchange and companies? relevant sector: the LinkedIn case study * *Victor Munoz. Wealth distribution for agents with spending propensity, interacting over a network * *Samuel Heroy, Nowell Phelps, Daniel Straulino and Neave O'Clery. Entrapment of microfinance adoption in dyads, communities, and castes * *Xiuxiu Zhan, Ziyu Li, Naoki Masuda, Petter Holme and Huijuan Wang. Susceptible-infected-spreading-based network embedding in static and temporal networks * *Javier Pardo-Diaz, Philip Poole, Mariano Beguerisse-D?az, Charlotte Deane and Gesine Reinert. Signed distance correlation to generate weighted and thresholded gene coexpression networks * *Anastasiya Salova and Raissa D'Souza. Cluster synchronization on hypergraphs * *Zakariya Ghalmane, Chantal Cherifi, Hocine Cherifi and Mohammed El Hassouni. A Community-Aware Backbone Extractor for Weighted Networks * *Arianna Pierdomenico, Anna Maria D'Arcangelis and Giulia Rotundo. Impact of Brexit on STOXX Europe 600 constituens. A complex network analysis * *Fuad Aleskerov, Alina Roman and Viacheslav Yakuba. Group Centrality Indices in the International Trade Networks * *Gabriele Pisciotta, Miriana Somenzi, Elisa Barisani and Giulio Rossetti. Sockpuppet Detection: a Telegram case study * *Masahiro Ikeda, Masahito Kumano, Joao Gama and Masahiro Kimura. Simplicial Closure in Significant Higher-Order Network among Cooking Ingredients * *Sarbendu Rakshit, Soumen Majhi and Dibakar Ghosh. Synchronization in complex networks with long-range interactions * *Samuel Martin-Gutierrez, Juan C. Losada and Rosa M. Benito. Impact of individual actions on the collective response of social systems * *Marijn ten Thij, Lauren Rutter, Lorenzo Lorenzo-Luaces and Johan Bollen. Revealing the complex comorbidity structure of internalizing disorders through hypergraph models * *Aymeric Vi? and Alfredo Morales. The hidden cost of interdependencies: Collapse of complex economic systems and network structure * *Gergely Palla, P?ter Pollner and Istv?n Csabai. Hierarchical properties and control of ageing-related methylation networks * *Lilia Perfeito and Joana Gon?alves-S?. A popularity model for information spreading: Twitter as a case study * *Natalia Rubanova and Nadya Morozova. Network analysis of functional genomics screening data * *Romain Pousse, Claire Lagesse and St?phane Douady. Modeling the urban network * *Yingkai Liu and Gabriel Cwilich. Mixed Strategies for Improving the Scale and Efficiency of Infection Tests using pool-testing * *Ilyes Abdelhamid, Alessandro Muscoloni and Carlo Cannistraci. The node2community prediction problem in complex networks * *Franz-Benjamin Mocnik. On the Effect of Space on the Spread of Infections * *Eva Barrena, Alicia De-Los-Santos, M Cruz L?pez-de-Los-Mozos and Juan A Mesa. Equality Measures in Complex Networks * *Ofer Biham, Eytan Katzav, Reimer Kuehn and Haggai Bonneau. Statistical properties of edges and bredges in configuration model networks * *Tam?s Sebesty?n and Zita Iloskics. Shock propagation channels behind the global economic contagion network * *Osnat Mokryn. The opinions of a few: A cross-platform study quantifying usefulness of reviews * *Andreia Sofia Teixeira, Joshua Faskowitz, Olaf Sporns and Luis M. Rocha. The Metric Backbone in the Human Connectome * *Gorka Zamora-L?pez and Matthieu Gilson. Unraveling the paradox of weak links in structural brain connectivity * *Gabriel Cwilich, Zvi Goldstein and Sergey V. Buldyrev. Distribution of the sizes of blackouts on electrical grids and some theoretical models * *William Schueller and Johannes Wachs. Dependency Networks and Systemic Risk in Open Source Software Ecosystems * *Sonali Chauhan, Gitanjali Yadav and Suresh Babu. Ecological networks reveal species associations and communities in Urban Forests of South Delhi Ridge, India * *Diego Ortega. Urban gentrification as an avalanche process * *Badhan Chandra Das, Md Musfique Anwar and Md. Al-Amin Bhuiyan. Query Oriented Temporal Active Community Search * *Alan Forero, Martha Bohorquez, Rafael Renteria and Jorge Mateu. Identification of Patterns for Space-Time Event Networks * *Gregorio Alanis-Lobato, Thomas Bartlett and Kathy Niakan. Multiomics-based inference of cell type-specific regulatory networks in early human embryos * *Vitalba Macaluso, Clara D'Apoli and Giulio Rossetti. Quarantined world through SoundCloud hashtags network * *Yitzchak Novick and Amotz Barnoy. Fair Comparisons Among Network Sampling Strategies * *Somaye Sheykhali, Fernandez-Gracia Fernandez-Gracia, Carlos M. Duarte and Victor M. Eguiluz. Inferring Eukaryote-Prokaryote interactions in microbial communities: a multi-layer network approach * *Jeremie Fish and Erik Bollt. A tail of two distributions: why most real world networks are negative binomial rather than power law. * *Tanguy Fardet and Anna Levina. Better weighted clustering coefficient: now continuous * *Tanjim Taharat Aurpa, Md Shoaib Ahmed and Md Musfique Anwar. Clustering Active Users in Twitter Based on Top-k Trending Topics * *Subhayan Mukerjee. A Network Model of Selective Exposure and Audience Behavior Using Community Detection * *Marco Cogoni and Giovanni Busonera. On the breakup patterns of urban networks under load * *Colin Burke. Digital Sousveillance: A Network Analysis Of US Surveillance Organizations * *Sara Ansari, Jobst Heitzig, Laura Brzoska, Hartmut Lentz, Jorg Fritzmier and Mohammad Reza Moosavi. Testing strategies for epidemic detection in livestock trade network * *Sotaro Sada and Yuichi Ikeda. Economic Integration Index Evaluated from Loop Flow Component in Global Value-Added Network * *Romain Lesauvage, Marcell Nagy and Roland Molontay. Calibrating Network Models for Real Networks Using graph2vec Embedding * *Milan Petrovi?, Ana Filo?evi? Vujnovi?, Rozi Andreti? Waldowski and Ana Mestrovic. Analysis of psychostimulant-induced group behaviours using network based framework in Drospophila melanogaster * *Giovanni Guarnieri Soares, Aurelienne Jorge, Jeferson Feitosa, Tanishq Garg, Kaushiki Dixit, Harshal Dupare, Vander Freitas and Leonardo Bacelar Lima Santos. Vulnerability indexes in complex networks as avulnerability component in disaster science * *Daniel Thilo Schroeder, Pedro G. Lind, Konstantin Pogorelov and Johannes Langguth. A Framework for Interaction-based Propagation Analysis in Online Social Networks * *Zaihan Yang and Dmitry Zinoviev. Detecting People Interested in Non-Suicidal Self-Injury on Social Media * *Valentina Baiamonte. Policy entrepreneurship and the structural conditions of policy diversity * *Daniel Pino, Jade Chattergoon, Aneeqah Hosein and Inzamam Rahaman. Comparing the efficacy of embeddings in Hyperbolic and Euclidean geometries with respect to the task of community detection. * *Denisse Pasten. Earthquake complex network analysis for the Mw 8.2 earthquake in Iquique, Chile * *Oded Cats and Anne Mijntje Hijner. Passenger Delay and Topological Indicators in Public Transport Networks * *Bal?zs R. Sziklai and Bal?zs Lengyel. Testing framework for proxy-based Influence maximization algorithms * *Norbert F?ron, Jason Vallet, Guy Melan?on, B?n?dicte Lavaud-Legendre, C?cile Plessard, Benjamin Renoust and Alexander Freeland. Avres: visualising multilayer networks for analysing human-trafficking networks * *Osnat Mokryn, David Bodoff, Nadim Bader, Yael Albo and Joel Lanir. Sharing emotions: Determining films' evoked emotional experience from their online reviews * *Leticia P?rez-Sienes, Julia Atienza-Barthelemy, Samuel Mart?n-Guti?rrez, Juan Carlos Losada and Rosa Mar?a Benito. Dynamical patterns of user activity during electoral campaigns and debates in Twitter * *Andrew Elliott, Stephen Law and Luis Ospina-Forero. Characterising road networks through subgraph graphlet analysis * *Matteo Zignani, Sabrina Gaito and Gian Paolo Rossi. Mobility Footprint of Cities Through an Epidemic Diffusion Model * *Sara Mesquita, L?lia Perfeito and Joana Gon?alves de S?. Using pandemic periods to improve now-casting modelsbased on search engine data * *Hendrik Nunner, Vincent Buskens and Mirjam Kretzschmar. Infectious disease dynamics in homophily-driven dynamic small-world networks: A model study. * *Mar?a ?ngeles Criado-Alonso, Elena Battaner-Moro, David Aleja, Miguel Romance and Regino Criado. Searching for linguistic collocations in specialty languages by using complex networks * *Abdel-Rahmen Korichi, Hamamache Kheddouci and Daniel West. Relationship graph for organisations using communication tools * *Marjan Cugmas, Franc Mali and Ale? ?iberna. Scientific collaboration of researchers and organizations: A two-level blockmodeling approach * *Maria Gracio, Sara Perestrelo, Nuno Ribeiro and Lu?s Lopes. Modelling spreading process of a wildfire in heterogeneous orography, fuel distribution and environmental conditions ? a multi-scale analysis using complex networks * *Julia Atienza-Barthlemy, Samuel Martin-Gutierrez, Juan Carlos Losada and Rosa M. Benito. Inferring political opinion and its relationship with use of language in a Twitter conversation around a territorial conflict * *Andrea Urgilez-Clavijo and Ana M. Tarquis. 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Graph Signal Processing on Complex Networksfor Structural Health Monitoring * *Henry Carscadden, Chris Kuhlman, Madhav Marathe, S. S. Ravi and Daniel Rosenkrantz. Blocking the Propagation of Two Simultaneous Contagions over Networks * *Miguel Rebollo, Rosa M. Benito, Juan Carlos Losada and Javier Galeano. Using Distributed Risk Maps by Consensus as a Complement to Contact Tracing Apps * *Thibaud Trolliet, Nathann Cohen, Fr?d?ric Giroire, Luc Hogie and St?phane P?rennes. Interest Clustering Coefficient: a New Metric for Directed Networks like Twitter * *Remy Cazabet. Data compression to choose a proper dynamic network representation * *Cecilia Toccaceli, Letizia Milli and Giulio Rossetti. Opinion Dynamic modeling of Fake News Perception * *Emily Kaven, Ilana Kaven, Diego Gomez-Zara, Leslie DeChurch and Noshir Contractor. Assessing how Team Task Influences Team Assembly Through Network Analysis * *Gerrit Gro?mann, Michael Backenk?hler, Jonas Klesen and Verena Wolf. Learning Vaccine Allocation from Simulations * *Lan Jiang, Ly Dinh, Rezvaneh Rezapour and Jana Diesner. Which groups do you belong to? Sentiment-based PageRank to measure formal and informal influence in social networks * *Mahdieh Zabihimayvan, Reza Sadeghi, Dipesh Kadariya and Derek Doran. Interaction of Structure and Information on Tor * *Jacob Grubb, Derek Lopez, Bhuvaneshwar Mohan and John Matta. Identifying Biomarkers for Important Nodes in an Epidemic * *Fr?d?ric Giroire, St?phane P?rennes and Thibaud Trolliet. A Random Growth Model with any Real or Theoretical Degree Distribution * *Steve Huntsman. Fast multipole networks * *Ardian Maulana and Hokky Situngkir. Media Partisanship during Election: Indonesian Cases * *Manqing Ma, Gyorgy Korniss and Boleslaw Szymanski. Learning Parameters for Balanced Index Influence Maximization * *Azwirman Gusrialdi. Distributed Algorithm for Link Removal in Directed Networks * *Zhongqi Cai, Markus Brede and Enrico Gerding. 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Local Degree Asymmetry for Preferential Attachment Model * *J?zsef Dombi and Sakshi Dhama. Using Preference Intensity for NetworkCommunities * *Chen Avin and Yuri Lotker. De-evolution of Preferential Attachment Trees * *Sebastian Me?nar, Nada Lavra? and Bla? ?krlj. Prediction of the effects of epidemic spreading with graph neural networks * *Leo Rannou, Cl?mence Magnien and Matthieu Latapy. Connected Components in Stream Graphs: Computation and Applications * *Yizhou Yan, Fujio Toriumi and Toshiharu Sugawara. Influence of Retweeting on the Behaviors of Social Networking Service Users * *Emre Sefer. Joint Modeling of Chromatin Marker Effects in 3D Genome Through Hi-C Interaction Graph * *Jan Treur. Self-Modeling Networks Using Adaptive Internal Mental Models for Cognitive Analysis and Support Processes * *Jingming Hu, Seok-Hee Hong, Jialu Chen, Marni Torkel, Peter Eades and Kwan-Liu Ma. Connectivity-based Spectral Sampling for Big Complex Network Visualization * *Mingshan Jia, Bogdan Gabrys and Katarzyna Musial. Closure Coefficient in Complex Directed Networks * *Joshua Priest, Madhav Marathe, S. S. Ravi, Daniel Rosenkrantz and Richard Stearns. Evolution of Similar Configurations in Graph Dynamical Systems * *Wenning Zhang, Ryohei Hisano, Takaaki Ohnishi and Takayuki Mizuno. Nondiagonal Mixture of Dirichlet Network Distributions for Analyzing a Stock Ownership Network * *Georgios Papagiannis and Sotiris Moschoyiannis. Deep Reinforcement Learning for Control of Probabilistic Boolean Networks * *Elise Henry, Mathieu Petit, Angelo Furno and Nour-Eddin El Faouzi. Quick Sub-optimal Augmentation of Large ScaleMulti-Modal Transport Networks * *Felipe Abrah?o, Klaus Wehmuth, Hector Zenil and Artur Ziviani. An Algorithmic Information Distortion in Multidimensional Networks * *Alessandro Muscolino, Antonio Di Maria, Salvatore Alaimo, Stefano Borz?, Paolo Ferragina, Alfredo Ferro and Alfredo Pulvirenti. NETME: On-the-fly knowledge network construction from biomedical literature * *Yasutaka Mizui, Shigeyuki Miyagi and Osamu Sakai. Statistics of Growing Chemical Network Originating from One Molecule Species and Activated by Low-Temperature Plasma * *Takahiro Miura, Kimitaka Asatani and Ichiro Sakata. Classifying Sleeping Beauties and Princes Using Citation Rarity * *Virgile Rennard, Giannis Nikolentzos and Michalis Vazirgiannis. Graph Auto-Encoders for Learning Edge Representations * *David Rivas-Tabares and Ana M. Tarquis Alfonso. Towards understanding complex interactions of Normalized Difference Vegetation Index and precipitation rain gauges networks of cereal growth system * *Joel Peito and Qiwei Han. Incorporating Domain Knowledge into Health Recommender Systems using Hyperbolic Embeddings * *Henrique Branquinho, Luciano Gr?cio and Pedro Ribeiro. StreamFaSE: an online algorithm for subgraph counting in dynamic networks * *Larry Yueli Zhang and Peter Marbach. Efficient Community Detection by Exploiting Structural Properties of Real-World User-Item Graphs * *Hugo Hourcade, Binh-Minh Bui-Xuan and C?dric Miachon. Computing Temporal Twins in Time Logarithmic in History Length * *Lucia Cavallaro, Annamaria Ficara, Francesco Curreri, Giacomo Fiumara, Pasquale De Meo, Ovidiu Bagdasar and Antonio Liotta. Graph comparison and artificial models for simulating real criminal networks * *Petr Chunaev, Timofey Gradov and Klavdiya Bochenina. Composite Modularity and parameter tuning in the weight-based fusion model for community detection in node-attributed social networks * *Sylvain Mignot and Annick Vignes. Trust somebody but choose carefully : an empirical analysis of social relationships on an exchange market * *Georgia Baltsou, Anastasios Gounaris, Apostolos N. Papadopoulos and Konstantinos Tsichlas. Towards Causal Explanations of Community Detection in Networks * *R?mi Segretain, Sergiu Ivanov, Laurent Trilling and Nicolas Glade. A Methodology for Evaluating the Extensibility of Boolean Networks' Structure and Function * *Bogumil Kaminski, Pawel Pralat and Francois Theberge. Community Detection Algorithm Using Hypergraph Modularity * *Gerrit Jan de Bruin, Cor Veenman, Jaap van Den Herik and Frank Takes. Experimental Evaluation of Train and Test Split Strategies in Link Prediction * *Alexandru Topirceanu. Analyzing the Impact of Geo-Spatial Organization of Real-World Communities On Epidemic Spreading Dynamics * *Rajesh Bhalwankar and Jan Treur. A Second-Order Adaptive Network Model for Learner-Controlled Mental Model Learning Processes * *Teru Fujii, Masahito Kumano, Joao Gama and Masahiro Kimura. Detecting Geographical Competitive Structure for POI Visit Dynamics * *Eisha Nathan. A Dynamic Algorithm for Linear Algebraically Computing Nonbacktracking Walk Centrality * *Yuki Yamagishi, Kazumi Saito, Kazuro Hirahara and Naonori Ueda. Spatio-Temporal Clustering of Earthquakes Based on Average Magnitudes * *Alexey L. Zaykov, Danila A. Vaganov and Valentina Y. Guleva. Diffusion dynamics prediction based on subgraph samples and motifs * *Stephany Rajeh, Marinette Savonnet, Eric Leclercq and Hocine Cherifi. Investigating Centrality Measures in Social Networks with Community Structure * *Mar?a ?skarsd?ttir, Jacky Mallett, Arn??r Logi Arnarson and Alexander Sn?r Stef?nsson. Analysis of tainted transactions in the Bitcoin Blockchain transaction network * *Andr?s Felipe Almeida ?au?ay, Rosa Mar?a Benito, Miguel Quemada, Juan Carlos Losada and Ana Mar?a Tarquis. Complexity of the vegetation-climate system through data analysis * *Mehrdad Agha Mohammad Ali Kermani, Samane Abbasi Sani and Hanie Zand. Resident?s Alzheimer disease and social networks within a nursing home * *Everson Pereira and Liang Zhao. Analysis of radiographic images of patients with COVID-19 using a complex network-based high-level classification technique * *Riccardo Dondi, Pietro Hiram Guzzi and Mohammad Mehdi Hosseinzadeh. Top-k Connected Overlapping Densest Subgraphs in Dual Networks * *Louis Duvivier, Remy Cazabet and Celine Robardet. Edge based stochastic block model statistical inference * *Mengzhen Li and Mehmet Koyuturk. Consensus Embeddings for Networks with Multiple Versions * *Majda Lafhel, Hocine Cherif, Benjamin Renoust, Mohammed El Hassouni and Youssef Mourchid. Movie Script Similarity using Multilayer Network Portrait Divergence * *Giorgio Locicero, Giovanni Micale, Alfredo Pulvirenti and Alfredo Ferro. TemporalRI: a subgraph isomorphism algorithm for temporal networks * *Ahlem Drif, Sami Guembour and Hocine Cherifi. A Sentiment Enhanced Deep Collaborative Filtering Recommender System * *Darkhan Medeuov, Camille Roth, Kseniia Puzyreva and Nikita Basov. Concept-centered comparison of semantic networks * *Ramya Gupta, Abhishek Prasad, Suresh Babu and Gitanjali Yadav. Temporal Bibliometric Networks on Coronavirus reveal Politics of the Pandemic * *Pau Vilimelis Aceituno. Eigenvalues of Random Graphs with Cycles * *Marzena Fugenschuh, Ralucca Gera and Andrea Tagarelli. Topological Analysis of Synthetic Models for Air Transportation Multilayer Networks * *Soroosh Shalileh and Boris Mirkin. A Method for Community Detection in Networks with Mixed Scale Features at its Nodes * *Rinat Aynulin and Pavel Chebotarev. Measuring Proximity in Attributed Networks for Community Detection * *Alexander Chepovskiy, Svetlana Khaykova and Dmitry Leshchev. Core Method for Community Detection * *Jiaqi Ren, Jun Guan and Lizhi Xing. Measuring the Nestedness of Global Production System based on Bipartite Network * *Lizhi Xing and Yu Han. Extracting the Backbone of Global Value Chain from High-Dimensional Inter-Country Input-Output Network * *Jueyi Liu, Yuze Sui, Ling Zhu and Xueguang Zhou. Modeling and Evaluating Hierarchical Network: An Application to Personnel Flow Network * *Hohyun Jung and Frederick Kin Hing Phoa. Analysis of a Finite Mixture of Truncated Zeta Distributions for Degree Distribution * *Shuto Araki and Aaron Bramson. Connecting the Dots: Integrating Point Location Data into Spatial Network Analyses * *Maham Mobin Sheikh and Rauf Ahmed Shams Malick. Community Detection in a Multi-layer Network Over Social Media * *Keigo Yamamoto, Shigeyuki Miyagi and Osamu Sakai. Order Estimation of Markov-Chain Processes in Complex Mobility Network Embedded in Vehicle Traces * *Theresa Migler, Lauren Nakamichi and Zo? Wood. An Analysis of Four Academic Department Collaboration Networks with Respect to Gender * *Hajime Miyazawa and Tsuyoshi Murata. Graph Convolutional Network with Time-based Mini-batch for Information Diffusion Prediction * *Ardian Maulana and Hokky Situngkir. Media Polarization on Twitter during 2019 Indonesian Election * *Alexios Mandalios, Alexandros Chortaras, Giorgos Stamou and Michalis Vazirgiannis. Enriching Graph Representations of Text: Application to Medical Text Classification * *Saharnaz Dilmaghani, Matthias R. Brust, Gregoire Danoy and Pascal Bouvry. Local Community Detection Algorithm with Self-defining Source Nodes * *Yitzchak Novick and Amotz Barnoy. Finding High-Degree Vertices with Inclusive Random Sampling * *Kazufumi Inafuku, Takayasu Fushimi and Tetsuji Satoh. Stimulation Index of Cascading Transmission in Information Diffusion over Social Networks * *Carlos Barbosa, Lucas F?lix, Ant?nio Alves, Carolina Xavier and Vin?cius Vieira. SaraBotTagger - a Light Tool to Identify Bots in Twitter * *Nako Tsuda and Sho Tsugawa. Effects of Community Structure in Social Networks on Speed of Information Diffusion * Join us at COMPLEX NETWORKS 2020 Madrid Spain *-------------------------* Hocine CHERIFI University of Burgundy Franche-Comt? Deputy Director LIB EA N? 7534 Editor in Chief Applied Network Science Editorial Board member PLOS One , IEEE ACCESS , Scientific Reports , Journal of Imaging , Quality and Quantity , Computational Social Networks , Complex Systems -------------- next part -------------- An HTML attachment was scrubbed... URL: From jerryzhu at cs.wisc.edu Thu Oct 8 12:00:21 2020 From: jerryzhu at cs.wisc.edu (JERRY ZHU) Date: Thu, 8 Oct 2020 16:00:21 +0000 Subject: Connectionists: Special Issue of IISE Transactions Data Analytics and Decision Making for Internet-of-Things (IoT) Enabled Systems In-Reply-To: References: , Message-ID: Call for Papers Special Issue of IISE Transactions Data Analytics and Decision Making for Internet-of-Things (IoT) Enabled Systems We are living in the age of IoT, where internet-of-things (IoT) enabled systems are ubiquitous. An IoT device, broadly defined, is a device connected to the internet, allowing users to access its data and to control its functions remotely. The ubiquitous availability of IoT devices has the great potential of bringing broad disruptive societal impacts, particularly on economic competitiveness, quality of life, public health, and essential infrastructure. For example, (1) In manufacturing systems, we can collect data from all the workstations to make system operations transparent and enable smart operation decisions to improve various key performance measures. (2) Through smart home appliances, we can obtain their usage pattern and then control their operations accordingly for enhancing home security and optimizing energy use. (3) By providing wearable devices to patients, we can monitor their physiological condition in real time and collect observations of daily living (ODL) data, which can be used for more accurate diagnosis and clinical intervention. (4) By observing the failure events from multiple units, we can establish a fleet-based reliability model and make individualized failure prognosis. In this IoT age, a large amount of data from multiple similar subjects/devices/machines are available in real time. The dimension and volume of the data collected is often very large and contains data of different fidelities and diverse types (data streams, images, videos, continuous, discrete, etc.). These features set forth the need to rethink many traditional predictive and prescriptive methods to adapt to (1) unique data features collected in IoT settings (2) the need for individualized inference while still leveraging information across subjects (3) real-time predictions and decisions often at very high frequencies. This special issue aims to publish original, significant, and visionary papers describing scientific methods and technologies with both solid theoretical development and practical importance for IoT enabled systems. Topics to be covered include, but are not limited to: ? Data analytics and machine learning methods for IoT enabled systems, such as individualized inference, hierarchical model, multitask learning, federated learning, physics-informed deep learning, online/active learning. ? Data driven decision-making methods for IoT enabled system operation optimization such as mathematical programming under uncertainty, real-time control, Markov decision making, reinforcement learning. ? Advanced quality control techniques for IoT enabled systems, e.g., online statistical monitoring, root cause identification, quality assessment and validation. ? Fleet-based system reliability and prognosis and maintenance decision-making ? Data driven IoT enabled operation-inventory-service decision-making and optimization ? IoT enabled supply chain management ? IoT-enabled system design and operations in service and manufacturing ? Cybersecurity and privacy in engineering systems ? IoT applications in smart manufacturing such as cloud manufacturing, production control and optimization ? IoT applications in healthcare such as real time patient monitoring and intervention, bystander tele-coaching during emergency rescue, remote medicine tracking and inventory control ? IoT applications in infrastructure, energy management, transportation, and vehicle telematics All papers are to be submitted through http://mc.manuscriptcentral.com/iietransactions. Please select ?Special Issue? under Manuscript Category of your submission. All manuscripts must be prepared according to the IISE Transactions publication guidelines. Important Dates ? Manuscript submission deadline March 1st, 2021 ? Notification of disposition of the manuscript May 1st, 2021 ? Revision due July 1st, 2021 ? Paper acceptance decision October 1st, 2021 ? Publication date Winter 2021 Guest Editors ? Professor Shiyu Zhou, University of Wisconsin-Madison, email: shiyuzhou at wisc.edu ? Professor Yong Chen, University of Iowa, email: yong-chen at uiowa.edu ? Professor Nan Kong, Purdue University, email: nkong at purdue.edu ? Professor Raed Al Kontar, University of Michigan, email: alkontar at umich.edu From pstone at cs.utexas.edu Thu Oct 8 17:17:38 2020 From: pstone at cs.utexas.edu (Peter Stone) Date: Thu, 08 Oct 2020 16:17:38 -0500 Subject: Connectionists: Machine Learning Postdocs at UT Austin Message-ID: <8274.1602191858@cs.utexas.edu> Colleagues, Multiple postdoctoral positions in Machine Learning are now available for 2021 at The University of Texas at Austin. For details, please see: https://ml.utexas.edu/postdoctoral-positions ___ Professor Peter Stone David Bruton, Jr. Centennial Professor University Distinguished Teaching Professor Associate Chair Department of Computer Science phone: 512-471-9796 The University of Texas at Austin fax: 512-471-8885 2317 Speedway, Stop D9500 pstone at cs.utexas.edu Austin, Texas 78712-1757 USA http://www.cs.utexas.edu/~pstone From li.zhaoping at tuebingen.mpg.de Fri Oct 9 06:22:01 2020 From: li.zhaoping at tuebingen.mpg.de (Zhaoping Li) Date: Fri, 9 Oct 2020 12:22:01 +0200 Subject: Connectionists: Ph.D. program in Computational/Experimental Neuroscience in Tuebingen, Germany Message-ID: Join our interdisciplinary PhD program and experience a vibrant and international training environment in Neuroscience! Image -- Li Zhaoping Ph.D. Prof. of Cognitive Science, University of Tuebingen Head of Dept of Sensory and Sensorimotor Systems, Max Planck Institute of Biological Cybernetics Author of "Understanding vision: theory, models, and data", Oxford University Press, 2014 www.lizhaoping.org -------------- next part -------------- An HTML attachment was scrubbed... URL: From Albrecht_Zimmermann at gmx.net Sat Oct 10 05:23:21 2020 From: Albrecht_Zimmermann at gmx.net (Albrecht Zimmermann) Date: Sat, 10 Oct 2020 11:23:21 +0200 Subject: Connectionists: Last weekend before SDM 2021 deadline Message-ID: An HTML attachment was scrubbed... URL: From fabio.bellavia at unifi.it Sun Oct 11 18:39:04 2020 From: fabio.bellavia at unifi.it (Fabio Bellavia) Date: Mon, 12 Oct 2020 00:39:04 +0200 Subject: Connectionists: [CFP] MAES2020 - still in time to submit papers not accepted to the ICPR2020 general session! Message-ID: <8a7652eb-9b72-d963-0b77-db244b131c40@unifi.it> ???????????????????? MAES2020 workshop at ICPR2020 ?????????? ---===== Apologies for multiple posting =====--- ?????????? Please distribute this call to interested parties _______________________________________________________________________ ??? Machine Learning Advances Environmental Science (MAES at ICPR2020) ??????????????????????????? workshop at the ??? 25th International Conference on Pattern Recognition (ICPR2020) ???????????????????? Milan, Italy, January 10, 2021 ????????? >>> https://sites.google.com/view/maes-icpr2020/ <<< ?? ? //????????? S U B M I S S I O N??? D E A D L I N E????????? \\ ?? ? \\?? E X T E N D E D??? T O??? 2 5??? O C T O B E R !!!???? // ?????? +++ UPDATES: the workshop will be taken FULLY VIRTUAL +++ ? *** PLEASE NOTE THAT PAPERS NOT ACCEPTED IN THE ICPR2020 GENERAL ** ?? **? SESSION AND FITTING MAES TOPICS COULD BE SUBMITTED HERE !!! *** ??? ----> https://easychair.org/conferences/?conf=maesicpr2020 <---- _______________________________________________________________________ ?=== Aim & Scope === Environmental data are growing steadily in volume, complexity and diversity to Big Data mainly driven by advanced sensor technology. Machine learning can offer superior techniques for unravelling complexity, knowledge discovery and predictability of Big Data environmental science. The aim of the workshop is to provide a state-of-the-art survey of environmental research topics that can benefit from Machine Learning methods and techniques. To this purpose the workshop welcomes papers on successful environmental applications of machine learning and pattern recognition techniques to? diverse domains of Environmental Research, for instance, recognition of biodiversity in thermal, photo and acoustic images, natural hazards analysis and prediction, environmental remote sensing, estimation of environmental risks, prediction of the concentrations of pollutants in geographical areas, environmental threshold analysis and predictive modelling, estimation of Genetical Modified Organisms (GMO) effects on non-target species. The workshop will be the place to make an analysis of the advances of Machine Learning for the Environmental Science and should indicate the open problems in environmental research that still have not properly benefited from Machine Learning. Extended papers of this workshop will be published as a special issue in the journal of Environmental Modelling and Software, Elsevier. *** Due to the COVID pandemic, the workshop will be taken fully virtual. All accepted papers will be published. *** ?=== Invited Talk === "Harnessing big environmental data by machine learning", prof. Friedrich Recknagel, School of Biological Sciences, University of Adelaide, Australia (prof. Recknagel's bio: http://www.adelaide.edu.au/directory/friedrich.recknagel) (talk abstract: https://drive.google.com/file/d/12BFBiG4pwN-6TRKCy0OuGHOgue4YbOKJ/view?usp=sharing) ?=== Important Dates === -? 25 October? 2020 - workshop submission deadline (*EXTENDED*) -? 10 November 2020 - author notification -? 15 November 2020 - camera-ready submission -?? 1 December 2020 - finalized workshop program ?=== Organizers === ? Francesco Camastra, Universita' di Napoli Parthenope, Italy ?Friedrich Recknagel, University of Adelaide, Australia ??? Antonino Staiano, Universita' di Napoli Parthenope, Italy ?== Publicity chair == ????? Fabio Bellavia, Universita' di Palermo, Italy _______________________________________________________________________ ?Contacts: antonino.staiano at uniparthenope.it ?????????? francesco.camastra at uniparthenope.it ?Workshop: https://sites.google.com/view/maes-icpr2020/ ?ICPR2020: https://www.micc.unifi.it/icpr2020/ From pablo.alvesdebarros at iit.it Mon Oct 12 05:13:13 2020 From: pablo.alvesdebarros at iit.it (Pablo Vinicius Alves De Barros) Date: Mon, 12 Oct 2020 09:13:13 +0000 Subject: Connectionists: Call For Abstracts - Workshop on Affective Shared Perception (WASP) (Deadline Extended!) Message-ID: <4b53150e9d2a40ab9f96d551e9e93e24@iit.it> Dear all, We are delighted to inform you that we have a deadline extension for abstract submission in our Workshop on Affective Shared Perception (WASP), hosted by the International Conference on Developmental Learning and Epigenetic Robotics (ICDL-EPIROB2020). Please find below all the information! Cheers, Pablo I. Aim and Scope Our perception of the world, in particular, the ones which are influenced by affective understanding, depends both on sensory perception and prior knowledge. Most of the current research on modeling affective behavior as computer models ground their contribution to pre-trained learning models, which are purely data-driven, or on reproducing existing human behavior. Such approaches allow for easily reproducible solutions that fail when applied to complex social scenarios. Understanding shared perception as part of the affective processing mechanisms will allow us to tackle this problem and to provide the next step towards a real-world affective computing system. The goal of this workshop is to present and discuss new findings, theories, systems, and trends in computational models of affective shared perception. The workshop will feature a multidisciplinary list of invited speakers with experience in different aspects of social interaction, which will allow a rich and diverse debate about our overarching theme of affective shared perception. The workshop is scheduled to happen on the 30th of October of 2020 virtually. It will start at 15h00 CET and it will have a total duration of 3h30min. The participation is free, and a Zoom room will be available shortly before the workshop starts. II. Registration The registration to the workshop is free, but to guarantee a place to attend the workshop, please register here: https://forms.office.com/Pages/ResponsePage.aspx?id=XkYvv3Ufb0u-Kb9TJzvB2u5KiGG9gI9Jl0u_PdkIVS5UODk0UE43V1VJQVgxQVlJWVo0R1g0WUxQMi4u III. Potential Topics Topics include, but are not limited to: - Affective perception and learning - Affective modulation and decision making - Developmental perspectives of shared perception - Machine learning for shared perception - Bio-inspired approaches for affective shared perception - Affective processing for embodied and cognitive robots - Multisensory modeling for conflict resolution in shared perception - New psychological findings on shared perception - Assistive aspects and applications of shared affective perception IV. Invited Speakers Prof. Dr. Ginevra Castellano - Uppsala University, Sweeden Prof. Dr. Ellen Souza - Federal Rural University of Pernambuco, Brazil Prof. Dr. Yukie Nagai - The University of Tokyo, Japan V. Submission Prospective participants in the workshop are invited to submit a contribution as an abstract with a maximum of 350 words. Submission information: https://www.whisperproject.eu/wasp2020 The abstracts will be peer-reviewed by experts from all over the world. To encourage the integration with the local affective computing communities, we will allow student abstracts to be submitted in English, Spanish, and Portuguese. Each accepted abstract will be presented as a 5 min video (in English!) that will be shared on the workshop's social media. During the workshop, all the videos will be streamed and the authors will have a joint live Q/A with the audience for 60minutes. Participants can also opt-in for participating in our Frontiers Research Topic on Affective Shared Perception ( https://www.frontiersin.org/research-topics/16086/affective-shared-perception). The same abstract sent to the workshop can be sent as an abstract submission to the research topic. If you want to opt-in for the research topic, only English submissions will be accepted. - Abstract submission deadline: 17th of October - Notification of acceptance: 19th of October - Frontiers Research Topic Abstract Deadline: 24th of October - Video submission: 24th of October VI. Organizers Pablo Vinicius Alves De Barros, Italian Institute of Technology (IIT), Genova, Italy Alessandra Sciutti, Italian Institute of Technology (IIT), Genova, Italy VII. Acknowledgment The workshop is organized in the framework of the Starting Grant wHiSPER (G.A. No 804388) funded by the European Research Council (ERC) under the European Union?s Horizon 2020 research and innovation programme. ---------------------------------------- Dr. Pablo Barros Postdoctoral Researcher - CONTACT Unit Istituto Italiano di Tecnologia ? Center for Human Technologies Via Enrico Melen 83, Building B 16152 Genova, Italy email: pablo.alvesdebarros at iit.it website: https://www.pablobarros.net twitter: @PBarros_br -------------- next part -------------- An HTML attachment was scrubbed... URL: From blextar at gmail.com Tue Oct 13 00:59:28 2020 From: blextar at gmail.com (Luca Rossi) Date: Tue, 13 Oct 2020 12:59:28 +0800 Subject: Connectionists: CFP S+SSPR 2020 [Deadline Extension + FREE event] Message-ID: Dear all, Please note that the paper submission deadline for S+SSPR has been extended to the 1st of November 2020. We would also like to remind you that, in light of the current pandemic situation and in order to broaden the participation to the conference, this edition of S+SSPR will be an ONLINE and FREE event. Looking forward to your submissions, S+SSPR organising committee === CALL FOR PAPERS IAPR Joint International Workshops on 13th Statistical Techniques in Pattern Recognition (SPR) 18th Structural and Syntactic Pattern Recognition Workshop (SSPR) Time and place: 19-22 January 2021, Online event Paper submission deadline: 1 November 2020 S+SSPR 2020 is a joint event organised by Technical Committee 1 (Statistical Pattern Recognition Technique) and Technical Committee 2 (Structural and Syntactical Pattern Recognition) of the International Association of Pattern Recognition (IAPR). Following the trend of previous editions, S+SSPR 2020 will be held in close proximity to the International Conference on Pattern Recognition (ICPR). Authors are invited to submit papers addressing topics in statistical, structural or syntactic pattern recognition and their applications. Accepted papers will be published in Springer?s Lecture Notes in Computer Science (LNCS) series. For details see: http://www.dais.unive.it/sspr2020/ -- Luca Rossi Lecturer in Artificial Intelligence School of Electronic Engineering and Computer Science Queen Mary University of London https://blextar.github.io/luca-rossi/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From albagarciaseco at gmail.com Mon Oct 12 15:34:30 2020 From: albagarciaseco at gmail.com (=?UTF-8?B?QWxiYSBHYXJjw61h?=) Date: Mon, 12 Oct 2020 21:34:30 +0200 Subject: Connectionists: CBMS 2021 - Call for Special Tracks, Deadline Nov. 6 Message-ID: ---------------------------------------------------------------------------------------------------- CBMS 2021 - CALL FOR SPECIAL TRACKS ---------------------------------------------------------------------------------------------------- The 34th IEEE International Symposium on Computer-Based Medical Systems (IEEE CBMS 2021) June 7 ? 9, 2021, Aveiro, Portugal https://linkprotect.cudasvc.com/url?a=https%3a%2f%2fcbms2021.pt&c=E,1,feIH4BBUJboiJYCavLt0wKOoVltdiNHZIHRPQnalrq7K6WchpbFwd6VIzUd5nYcQrSq0FYNgUwp_oI7BUDdIj-K2wTwqCKtQoX6QgoMyzC1O9pVmqQ48G46k_Q,,&typo=1 ---------------------------------------------------------------------------------------------------- The IEEE International Symposium on Computer-Based Medical Systems (IEEE CBMS2021), now in its 34th edition, is the premier conference for computer-based medical systems, and one of the main conferences within the fields of medical informatics and biomedical informatics. IEEE CBMS 2021 invites proposals for organization of special tracks that will be held in parallel with the general conference track. The themes of the special tracks should not overlap with the general conference topics and should focus on emerging research fields. All tracks are expected to enable stimulating discussions of state-of-the-art, emerging, visionary, and perhaps controversial topics. Their papers should report on significant unpublished work and must meet the same standards as main conference papers. All accepted papers will be included in the conference proceedings. We expect all accepted tracks to adhere to the conference paper submission and reviewing schedule, as outlined in the dates indicated below. Special Tracks chair(s) will be interacting with organisers of accepted workshops to ensure a high quality workshop program. ---------------------------------------------------------------------------------------------------- SUBMISSION GUIDELINES ---------------------------------------------------------------------------------------------------- If you are interested in organizing a Special Track (ST), please submit your proposal by email to cbms2021 at ua.pt, using "CBMS2021 Special Track Proposal" in the subject line. Each proposal must include: 1. Special track title 2. Rough estimate of the expected ST size as number of sessions (with 4-5 papers per session) 3. A brief biography of ST organizer(s) 4. List of Special Track program committee members 5. A draft of Special Track ?Call for papers? 6. One or two appropriate journals or follow up publications: tracks are expected to organize a special issue ---------------------------------------------------------------------------------------------------- IMPORTANT DATES ---------------------------------------------------------------------------------------------------- Deadline for special track and tutorial proposal: November 6, 2020 Special track and tutorial notification acceptance: November 13, 2020 Paper submission deadline: February 5, 2021 Notification of acceptance: March 26, 2021 Deadline for final versions and conference registration: April 16, 2021 Conference dates: June 7-9, 2021 ---------------------------------------------------------------------------------------------------- Special Tracks Chairs ---------------------------------------------------------------------------------------------------- Alejandro Pazos Sierra, University of A Coru?a, Spain Alba Garcia Seco De Herrera, University of Essex, England KC Santosh, University of South Dakota, United States -------------- next part -------------- An HTML attachment was scrubbed... URL: From jncor at dei.uc.pt Mon Oct 12 16:57:45 2020 From: jncor at dei.uc.pt (=?UTF-8?Q?Jo=C3=A3o_Nuno_Correia?=) Date: Mon, 12 Oct 2020 21:57:45 +0100 Subject: Connectionists: Last CfP EvoStar 2021 - The Leading European Event on Bio-Inspired Computation - Seville, Spain. 7-9 April 2021 Message-ID: Dear Colleague(s), Below you will find the updated and last call for papers for EvoStar 2021. Feel free to distribute. Thank you for your time! ------------------------------------------------ Last Call for papers for the EvoStar conference http://www.evostar.org/2021/ Submission Deadline: November 1, 2020 Conference: 7 to 9 April 2021. Venue: Seville, Spain All accepted papers will be printed in the proceedings published by Springer Verlag in the Lecture Notes in Computer Science (LNCS) series. Please distribute (Apologies for cross-posting) ------------------------------------------------ ***************************************** News: - EvoStar goes Hybrid! The Evostar is planned as a hybrid event (online and onsite) from 7 to 9 April 2021. - Submission link is now open! https://easychair.org/my/conference?conf=evo2021 - Fast track publication in the Evolutionary Computation journal (MIT Press) for EvoCOP2021: The best regular paper presented at EvoCOP 2021 will be distinguished with a Best Paper Award. Authors nominated for the best regular paper award will be invited for fast track publication in the Evolutionary Computation journal (MIT Press). The invited submissions must significantly extend the conference paper and will undergo peer review. - Special Issue for EvoMUSART2021: Genetic Programming and Evolvable Machines (Q2, IF: 1.78) will publish a Special Issue on ?Evolutionary computation in Art, music & Design? edited by Juan Romero and Penousal Machado. Some authors from EvoMUSART 2021 will be invited to submit a new paper to this Special Issue. Information at: http://www.evostar.org/2021/evomusart/ - EvoApps: Special Sessions: http://www.evostar.org/2021/evoapps/ Confirmed Special Sessions: .Applications of Bioinspired techniques on Social Networks .Applications of Deep Bioinspired Algorithms .Applications of Nature-inspired Computing for Sustainability and Development .Evolutionary Computation in Image Analysis, Signal Processing and Pattern Recognition .Evolutionary Machine Learning .Machine Learning and AI in Digital Healthcare and Personalized Medicine .Parallel and Distributed Systems .Soft Computing Applied to Games ****************************************** EvoStar comprises four co-located conferences run each spring at different locations throughout Europe. These events arose out of workshops originally developed by EvoNet, the Network of Excellence in Evolutionary Computing, established by the Information Societies Technology Programme of the European Commission, and they represent a continuity of research collaboration stretching back over 20 years. EvoStar is organised by SPECIES, the Society for the Promotion of Evolutionary Computation in Europe and its Surroundings. This non-profit academic society is committed to promoting evolutionary algorithmic thinking, with the inspiration of parallel algorithms derived from natural processes. It provides a forum for information and exchange. The four conferences include: - EuroGP 24th European Conference on Genetic Programming http://www.evostar.org/2021/eurogp/ - EvoApplications 24th European Conference on the Applications of Evolutionary and bio-inspired Computation http://www.evostar.org/2021/evoapps/ - EvoCOP 21st European Conference on Evolutionary Computation in Combinatorial Optimisation http://www.evostar.org/2021/evocop/ - EvoMUSART 10th International Conference (and 15th European event) on Artificial Intelligence in Music, Sound, Art and Design. http://www.evostar.org/2021/evomusart/ *** Important Dates, Venue and Publication *** Submission Deadline: November 1, 2020 Conference: 7 to 9 April 2021. Venue: Seville, Spain All accepted papers will be printed in the proceedings published by Springer Verlag in the Lecture Notes in Computer Science (LNCS) series. Submission link: https://easychair.org/my/conference?conf=evo2021 Please, check the website for more information: http://www.evostar.org/2021/ And follow us at: Facebook - https://www.facebook.com/evostarconf/ Twitter - https://twitter.com/EvostarConf/ Instagram - https://www.instagram.com/evostarconference/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From torcini at gmail.com Tue Oct 13 04:41:24 2020 From: torcini at gmail.com (A. Torcini) Date: Tue, 13 Oct 2020 10:41:24 +0200 Subject: Connectionists: Exact mean field formulation of complex (neural) networks - Satellite CCS2020 Message-ID: Exact mean field formulation of complex (neural) networks December 9th, 2020 - CCS2020: The Conference on Complex Systems 2020 , Satellite Event ONLINE https://perso.u-cergy.fr/~atorcini/CCS2020/ccs20.html We are happy to announce the following satellite workshop Exact mean field formulation of complex (neural) networks to be held online on December 9th, 2020 within the CCS2020: The Conference on Complex Systems 2020 (http://ccs2020.web.auth.gr/). Topic: The brain activity is the paradigmatic example of the dynamics of an extremely complex network of networks, where large heterogeneous neural populations interact over different time and spatial scales. A first step in the simplification of this dynamics amounts to reproducing the neural population dynamics at a mean field level and this has led to the development of neural mass and neural field models of increasing complexity. Recent advances on coupled phase oscillators have allowed to reduce the evolution of in-principle infinite dimensional systems to the dynamics of a few macroscopic variables. This exact reduction methodology has been recently applied to neural spiking networks leading to the development of an extremely active research field aiming to develop a new generation of neural mass models. Invited Speakers: Aine Byrne, Carlo Laing , Denis Goldobin, Matteo di Volo, Halgurd Taher, Diego Pazo', Tilo Schwalger, Serhiy Yanchuk, Francesco Marino, Erik A. Martens The meeting is open to all the interested PhD students and researchers, however registration to the workshop and/or conference is mandatory (fees range from 20 euros to 180 euros). Early-bird registration is possible within November, 16th 2020 at this link: http://ccs2020.web.auth.gr/registration The Organizers: Simona Olmi (Inria Sophia Antipolis, France) Alessandro Torcini (LPTM, CY Cergy Paris University, France) From ioannakoroni at csd.auth.gr Tue Oct 13 05:50:18 2020 From: ioannakoroni at csd.auth.gr (Ioanna Koroni) Date: Tue, 13 Oct 2020 12:50:18 +0300 Subject: Connectionists: =?utf-8?q?CfP_1st_Autonomous_Vehicle_Vision_=28AV?= =?utf-8?q?Vision=E2=80=9921=29_Workshop_=28In_conjunction_with_WAC?= =?utf-8?q?V_2021=29?= References: <006301d6a138$ee1fa4a0$ca5eede0$@csd.auth.gr> Message-ID: <010e01d6a146$43148810$c93d9830$@csd.auth.gr> Call for Papers 1st Autonomous Vehicle Vision (AVVision?21) Workshop In conjunction with WACV 2021 The Autonomous Vehicle Vision 2021 (AVVision?21) workshop (webpage: avvision.xyz) aims to bring together industry professionals and academics to brainstorm and exchange ideas on the advancement of visual environment perception for autonomous driving. In this one-day workshop, we will have regular paper presentations and invited speakers to present the state of the art as well as the challenges in autonomous driving. Furthemore, we have prepared several large-scale, synthetic and real-world datasets, which have been annotated by the Hong Kong University of Science and Technology (HKUST), UDI, CalmCar, ATG Robotics, etc. Based on these datasets, three challenges will be hosted to understand the current status of computer vision and machine/deep learning algorithms in solving the visual environment perception problems for autonomous driving: 1) CalmCar MTMC Challenge, 2) HKUST-UDI UDA Challenge, and 3) KITTI Object Detection Challenge. Keynote Speakers: ? Andreas Geiger, University of T?bingen ? Ioannis Pitas, Aristotle University of Thessaloniki ? Nemanja Djuric, Uber ATG ? Walterio Mayol-Cuevas, University of Bristol & Amazon Call for Papers: With a number of breakthroughs in autonomous system technology over the past decade, the race to commercialize self-driving cars has become fiercer than ever. The integration of advanced sensing, computer vision, signal/image processing, and machine/deep learning into autonomous vehicles enables them to perceive the environment intelligently and navigate safely. Autonomous driving is required to ensure safe, reliable, and efficient automated mobility in complex uncontrolled real-world environments. Various applications range from automated transportation and farming to public safety and environment exploration. Visual perception is a critical component of autonomous driving. Enabling technologies include: a) affordable sensors that can acquire useful data under varying environmental conditions, b) reliable simultaneous localization and mapping, c) machine learning that can effectively handle varying real-world conditions and unforeseen events, as well as ?machine-learning friendly? signal processing to enable more effective classification and decision making, d) hardware and software co-design for efficient real-time performance, e) resilient and robust platforms that can withstand adversarial attacks and failures, and f) end-to-end system integration of sensing, computer vision, signal/image processing and machine/deep learning. The AVVision'21 workshop will cover all these topics. Research papers are solicited in, but not limited to, the following topics: * 3D road/environment reconstruction and understanding; * Mapping and localization for autonomous cars; * Semantic/instance driving scene segmentation and semantic mapping; * Self-supervised/unsupervised visual environment perception; * Car/pedestrian/object/obstacle detection/tracking and 3D localization; * Car/license plate/road sign detection and recognition; * Driver status monitoring and human-car interfaces; * Deep/machine learning and image analysis for car perception; * Adversarial domain adaptation for autonomous driving; * On-board embedded visual perception systems; * Bio-inspired vision sensing for car perception; * Real-time deep learning inference. Author Guidelines: Authors are encouraged to submit high-quality, original (i.e. not been previously published or accepted for publication in substantially similar form in any peer-reviewed venue including journal, conference or workshop) research. The paper template is identical to the WACV2020 main conference. The author toolkit (latex only) is available both on Overleaf and in Github. The submissions are handled through the CMT submission website: https://cmt3.research.microsoft.com/AVV2021/. Papers presented at the WACV workshops will be published as part of the "WACV Workshops Proceedings" and should, therefore, follow the same presentation guideliness as the main conference. Workshop papers will be included in IEEE Xplore, but will be indexed separatelly from the main conference papers. For questions/remarks regarding the submission e-mail: avv.workshop at gmail.com . Challenges: Challenge 1: CalmCar MTMC Challenge Multi-target multi-camera (MTMC) tracking systems can automatically track multiple vehicles using an array of cameras. In this challenge, participants are required to design robust MTMC algorithms, which are targeted at vehicles, where the same vehicles captured by different cameras possess the same tracking IDs. The competitors will have access to four large-scale training datasets, each of which includes around 1200 annotated RGB images, where the labels cover the types of vehicles, tracking IDs and 2D bounding boxes. Identification precision (IDP) and identification recall (IDR) will be used as metrics to evaluate the performance of the implemented algorithms. The competitors are required to submit their pretrained models as well as the corresponding docker image files via the CMT submission system for algorithm evaluation (in terms of both speed and accuracy). The winner of the competition will receive a monetary prize (US$5000) and will give a keynote presentation at the workshop. Challenge 2: HKUST-UDI UDA Challenge Deep neural networks excel at learning from large amounts of data but they can be inefficient when it comes to generalizing and applying learned knowledge to new datasets or environments. In this competition, participants need to develop an unsupervised domain adaptation (UDA) framework which can allow a model trained on a large synthetic dataset to generalize to real-world imagery. The tasks in this competition include: 1) UDA for monocular depth prediction and 2) UDA for semantic driving-scene segmentation. The competitors will have access to Ready to Drive (R2D) dataset, which is a large-scale synthetic driving scene dataset collected under different weather/illumination conditions using the Carla Simulator. In addition, competitors will also have access to a small amount of real-world data. The mean absolute value of the relative (mAbsRel) error and the mean intersection over union (mIoU) score will be used as metrics to evaluate the performance of UDA for monocular depth prediction and UDA for semantic driving scene segmentation, respectively. The competitors will be required to submit their pretrained models and docker image files via the CMT submission system. Challenge 3: KITTI Object Detection Challenge Researchers of top-ranked object detection algorithms submitted to the KITTI Object Detection Benchmarks will have the opportunity to present their work at AVVision'21, subject to space availability and approval by the workshop organizers. It should be noted that only the algorithms submitted before 12/20/2020 are eligible for presentation at AVVision'21. Important Dates: Full Paper Submission: 11/02/2020 Notification of Acceptance: 11/23/2020 Camera-Ready Paper Due: 11/30/2020 HKUST-UDI UDA Challenge abstract and code submission: 12/13/2020 Notification of HKUST-UDI UDA Challenge results: 12/20/2020 CalmCar MTMC Challenge abstract and code submission: 12/13/2020 Notification of CalmCar MTMC Challenge results: 12/20/2020 -- This email has been checked for viruses by Avast antivirus software. https://www.avast.com/antivirus -------------- next part -------------- An HTML attachment was scrubbed... URL: From darksnail at gmail.com Tue Oct 13 06:57:58 2020 From: darksnail at gmail.com (darksnail at gmail.com) Date: Tue, 13 Oct 2020 10:57:58 +0000 Subject: Connectionists: Canceled event: Registration open for the Simons-Emory Wo... @ Fri Dec 4, 2020 17:00 - 20:00 (CET) (connectionists@cs.cmu.edu) Message-ID: <000000000000abbfb305b18b492e@google.com> This event has been canceled. Title: Connectionists: Registration open for the Simons-Emory Workshop on Neural Dynamics Dear all, Registration is now open for the Simons-Emory Workshop on Neural Dynamics, which will livestream on Friday, December 4th from 11am-2pm EST. Please go here to register [1] "What could neural dynamics have to say about neural computation, and do we know how to listen?" Speakers will deliver focused 10-minute talks, with periods reserved for broader discussion on topics at the intersection of neural dynamics and computation. The website for the event is here [2] Organizer and Moderator: Chethan Pandarinath - ( Emory University and Georgia Tech ) Speakers & Discussants: Adrienne Fairhall - U Washington Mehrdad Jazayeri - MIT John Krakauer - John Hopkins Francesca Mastrogiuseppe - Gatsby / UCL Abigail Person - U Colorado Abigail Russo - Princeton Krishna Shenoy - Stanford Saurabh Vyas - Columbia We look forward ... When: Fri Dec 4, 2020 17:00 ? 20:00 Central European Time - Rome Joining info: Join with Google Meet https://meet.google.com/tsp-tgor-zia Calendar: connectionists at cs.cmu.edu Who: * darksnail at gmail.com - organizer Invitation from Google Calendar: https://www.google.com/calendar/ You are receiving this courtesy email at the account connectionists at cs.cmu.edu because you are an attendee of this event. To stop receiving future updates for this event, decline this event. Alternatively you can sign up for a Google account at https://www.google.com/calendar/ and control your notification settings for your entire calendar. Forwarding this invitation could allow any recipient to send a response to the organizer and be added to the guest list, or invite others regardless of their own invitation status, or to modify your RSVP. Learn more at https://support.google.com/calendar/answer/37135#forwarding -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: not available Type: text/calendar Size: 1893 bytes Desc: not available URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: invite.ics Type: application/ics Size: 1932 bytes Desc: not available URL: From darksnail at gmail.com Tue Oct 13 06:57:01 2020 From: darksnail at gmail.com (darksnail at gmail.com) Date: Tue, 13 Oct 2020 10:57:01 +0000 Subject: Connectionists: Invitation: Registration open for the Simons-Emory Wo... @ Tue Oct 13 17:00 - Fri Dec 4, 2020 20:00 (CEST) (connectionists@cs.cmu.edu) Message-ID: <000000000000512c1305b18b46e5@google.com> You have been invited to the following event. Title: Connectionists: Registration open for the Simons-Emory Workshop on Neural Dynamics Dear all, Registration is now open for the Simons-Emory Workshop on Neural Dynamics, which will livestream on Friday, December 4th from 11am-2pm EST. Please go here to register [1] "What could neural dynamics have to say about neural computation, and do we know how to listen?" Speakers will deliver focused 10-minute talks, with periods reserved for broader discussion on topics at the intersection of neural dynamics and computation. The website for the event is here [2] Organizer and Moderator: Chethan Pandarinath - ( Emory University and Georgia Tech ) Speakers & Discussants: Adrienne Fairhall - U Washington Mehrdad Jazayeri - MIT John Krakauer - John Hopkins Francesca Mastrogiuseppe - Gatsby / UCL Abigail Person - U Colorado Abigail Russo - Princeton Krishna Shenoy - Stanford Saurabh Vyas - Columbia We look forward ... When: Tue Oct 13 17:00 ? Fri Dec 4, 2020 20:00 Central European Time - Rome Joining info: Join with Google Meet https://meet.google.com/tsp-tgor-zia Calendar: connectionists at cs.cmu.edu Who: * darksnail at gmail.com - organizer * amanda.louise.jacob at emory.edu * connectionists at cs.cmu.edu Event details: https://www.google.com/calendar/event?action=VIEW&eid=MjN0cXRqOWo5anVzdm9jdGxycXBwOGFjZDggY29ubmVjdGlvbmlzdHNAY3MuY211LmVkdQ&tok=MTkjZGFya3NuYWlsQGdtYWlsLmNvbTM5N2U1YjRjOWNlNjQ5NDZkNTIwMjcyM2IyZjVkNDdkMGE0NzQ0NTc&ctz=Europe%2FRome&hl=en&es=0 Invitation from Google Calendar: https://www.google.com/calendar/ You are receiving this courtesy email at the account connectionists at cs.cmu.edu because you are an attendee of this event. To stop receiving future updates for this event, decline this event. Alternatively you can sign up for a Google account at https://www.google.com/calendar/ and control your notification settings for your entire calendar. Forwarding this invitation could allow any recipient to send a response to the organizer and be added to the guest list, or invite others regardless of their own invitation status, or to modify your RSVP. Learn more at https://support.google.com/calendar/answer/37135#forwarding -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: not available Type: text/calendar Size: 2534 bytes Desc: not available URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: invite.ics Type: application/ics Size: 2584 bytes Desc: not available URL: From cognitivium at sciencebeam.com Tue Oct 13 07:14:37 2020 From: cognitivium at sciencebeam.com (Maryam) Date: Tue, 13 Oct 2020 14:44:37 +0330 Subject: Connectionists: Online Mentoring Job Offer Message-ID: <202010131114.09DBEd0K104419@scs-mx-01.andrew.cmu.edu> WE WANT YOU ! ScienceBeam, which is a designer and manufacturer of neuroscience applications and organizer of neuroscience educational courses, is looking for professional, experienced and authentic mentors from all around the world for online courses. Required fields: ? Neuroscience ? Neuro-Biofeedback ? EEG/ERP/QEEG ? Cognitive Science ? Programming (MATLAB, Bio-Signal processing, etc.) If you are as passionate about mentoring as you are about the above-mentioned fields, and can give a few hours per week in return for an honorarium, we would love to hear from you. Apply now and send your resumes to: workshop at sciencebeam.com WhatsApp No: +8613380781282 -------------- next part -------------- An HTML attachment was scrubbed... URL: From evomusart at gmail.com Tue Oct 13 09:37:25 2020 From: evomusart at gmail.com (EvoMUSART 2021) Date: Tue, 13 Oct 2020 15:37:25 +0200 Subject: Connectionists: Call for Papers - EvoMUSART 2021 - 10th International Conference on Artificial Intelligence in Music, Sound, Art and Design (Seville, Spain, 7-9 April 2021) Message-ID: ------------------------------------------------ Call for papers for the 10th International Conference on Artificial Intelligence in Music, Sound, Art and Design (EvoMUSART) Please distribute (apologies for cross-posting) ------------------------------------------------ The 10th International Conference on Artificial Intelligence in Music, Sound, Art and Design (EvoMUSART) will be held in Seville, Spain, on 7-9 April 2021, as part of the evo* event. EvoMUSART webpage: www.evostar.org/2021/evomusart Submission link: https://easychair.org/my/conference?conf=evo2021 Special Issue on Genetic Programming and Evolvable Machines The journal ?Genetic Programming and Evolvable Machines" (Q2, IF: 1.78) will publish a Special Issue called ?Evolutionary computation in Art, music & Design?. The editors of this Special Issue will be Juan Romero and Penousal Machado. Some authors from EvoMUSART 2021 will be invited to submit a new paper to this Special Issue. The main goal of EvoMUSART is to bring together researchers who are using Artificial Intelligence techniques (e.g. Artificial Neural Network, Evolutionary Computation, Swarm, Cellular Automata, Alife) for artistic tasks such as Visual Art, Music, Architecture, Video, Digital Games, Poetry, or Design. The conference gives researchers in the field the opportunity to promote, present and discuss ongoing work in the area. Accepted papers will be published by Springer Verlag in the Lecture Notes in Computer Science series. IMPORTANT DATES Submission deadline: 1 November 2020 Conference: 7-9 April 2021 We welcome submissions which use Artificial Intelligence techniques in the generation, analysis and interpretation of Art, Music, Design, Architecture and other artistic fields. Submissions must be at most 16 pages long, in Springer LNCS format. Each submission must be anonymised for a double-blind review process. The deadline for submission is 1 November 2020. Accepted papers will be presented orally or as posters at the event and included in the EvoMUSART proceedings published by Springer Verlag in a dedicated volume of the Lecture Notes in Computer Science series. Indicative topics include but are not limited to: * Systems that create drawings, images, animations, sculptures, poetry, text, designs, webpages, buildings, etc.; * Systems that create musical pieces, sounds, instruments, voices, sound effects, sound analysis, etc.; * Systems that create artefacts such as game content, architecture, furniture, based on aesthetic and/or functional criteria; * Systems that resort to artificial intelligence to perform the analysis of image, music, sound, sculpture, or some other types of artistic object; * Systems in which artificial intelligence is used to promote the creativity of a human user; * Theories or models of computational aesthetics; * Computational models of emotional response, surprise, novelty; * Representation techniques for images, videos, music, etc.; * Surveys of the current state-of-the-art in the area; * New ways of integrating the user in the process (e.g. improvisation, co-creation, participation). Submission link: https://easychair.org/my/conference?conf=evo2021 More information on the submission process and the topics of EvoMUSART can be found at: www.evostar.org/2021/evomusart Papers published in EvoMUSART can be found at: https://evomusart-index.dei.uc.pt We look forward to seeing you in Seville in 2021! The EvoMUSART 2021 organisers Juan Romero Tiago Martins Nereida Rodr?guez-Fernandez (publication chair) -------------- next part -------------- An HTML attachment was scrubbed... URL: From marcin at amu.edu.pl Tue Oct 13 16:51:20 2020 From: marcin at amu.edu.pl (Marcin Paprzycki) Date: Tue, 13 Oct 2020 22:51:20 +0200 Subject: Connectionists: Researcher/Programmer Positions EU funded project form the ICT-56 call In-Reply-To: <34b74733-541a-3410-f916-d325e54de718@amu.edu.pl> References: <34b74733-541a-3410-f916-d325e54de718@amu.edu.pl> Message-ID: <1ed82be3-bc7c-97b1-cb8c-26fd65986d5d@amu.edu.pl> Multiple Researcher/Programmer Positions Systems Research Institute Polish Academy of Sciences announces multiple researcher/programmer positions, within the scope of the ASSIST-IoT project (Architecture for Scalable, Self-*, human-centric, Intelligent, Secure, and Tactile next generation IoT). More information about the project can be found at: https://cordis.europa.eu/project/id/957258. Successful candidates will be strongly encouraged to start/follow work on their PhD thesis, in the framework of a doctoral school, or otherwise. We are looking for highly motivated individuals, with very good technical skills, who would like to contribute to the project, while having an opportunity to pursue their Ph.D., with research objectives devoted to topics like AI/ML, data/stream analytics, semantics, tactile IoT, etc. Required qualifications: ? Completed M.Sc. Degree in Computer Engineering (preferred) or Computer Science ? In-depth practical knowledge of technologies (languages, frameworks, tools) related to the scope of the project ? Pertinent industrial experience (highly desirable) ? Knowledge of English at an advanced level Application should consist of: ? CV (including comprehensive description of technical skills, and experiences) ? List of publications (if applicable) ? Master thesis ? Motivation letter ? providing detailed description of interests as related to the project First, the applications will be evaluated with respect to the, mentioned above, qualifications, and the match between candidates profile and the scope of the project. Next, prospective candidates will be invited to an (online) interview. Application deadline (strict): November 15, 2020 Applications (and inquiries) should be addressed to: Maria Ganzha, Ph.D., D.Sc. maria.ganzha at ibspan.waw.pl From compsens at medizin.uni-tuebingen.de Wed Oct 14 05:17:26 2020 From: compsens at medizin.uni-tuebingen.de (Compsens) Date: Wed, 14 Oct 2020 11:17:26 +0200 Subject: Connectionists: =?utf-8?q?PhD_Student_/_Postdoc_positions_in_Theo?= =?utf-8?q?retical_Neuroscience=2C_University_of_T=C3=BCbingen?= Message-ID: <20201014111726.Horde.ej3-tgHUHRVGgjelew3Vvji@webmail.uni-tuebingen.de> PhD Student / Postdoc positions in Theoretical Neuroscience, Hertie Institute for Clinical Brain Research / Center for Integrative Neuroscience, University of T?bingen The positions are part of the ERC-Synergy grant RELEVANCE that investigates the neural and computational processing of bodies, which is realized in collaboration with the Universities of Leuven and Maastricht. The project aims at the investigation of the computational neural mechanisms of the visual processing of social stimuli, combining theoretical modeling with experimental research in physiology and imaging in humans as well as in animal models (realized by the other partners). The theoretical work will combine neural network modeling, machine learning, and advanced methods for stimulus control from computer graphics. We are looking for individuals with an interest, or possibly even partial expertise in one or multiple of the following areas: - physiologically-inspired neural modeling or neural data analysis - deep learning, biologically-inspired neural networks - machine learning with applications in cognitive science - motion capture and tracking - computer animation, virtual reality, game engines (e.g. Unreal, Unity) In addition, we are looking for individuals with interest to develop computer-animation or virtual reality technology for non-standard applications. Successful students / postdocs will be integrated in the research taking place in the Section for Computational Sensomotorics (http://www.compsens.uni-tuebingen.de/), which is part of the Dept. of Cognitive Neurology. The group works on neural modeling, machine learning techniques related to social recognition, computer animation, and human motion modeling, e.g. realizing highly-realistic avatars and VR applications for experiments in neuroscience and clinical research. The group is part of the CyberValley initiative (https://cyber-valley.de/) that links groups related to machine learning and industry applications in T?bingen. Talented students will have the opportunity to pursue a PhD in the International Max Planck Research Schools or for ?Mechanisms of Mental Function and Dysfunction? at the Graduate Training Center for Neuroscience (https://www.neuroschool-tuebingen.de/), or at the International Max Planck Research School for Intelligent Systems (https://imprs.is.mpg.de/). Requirements: Candidates should have a (research) master degree in one of the following disciplines: (Biomedical) Engineering, Computer Science, (Cognitive) Neuroscience, Mathematics, Physics, or Computer Animation/Visual Effects. In addition to these requirements, candidates should have a theoretical interest in the area of visual neuroscience, and experience with scientific programming (Matlab, Python, or any other language), as well as basic programing languages such as C++. Additional information: Section for Computational Sensomotorics, Dept. for Cognitive Neurology, Hertie Institute for Clinical Brain Research & Centre for Integrative Neuroscience, University Clinic T?bingen. Email: martin.giese at uni-tuebingen.de. Web: http://www.compsens.uni-tuebingen.de/ From mpavone at dmi.unict.it Wed Oct 14 04:08:05 2020 From: mpavone at dmi.unict.it (Mario Pavone) Date: Wed, 14 Oct 2020 10:08:05 +0200 Subject: Connectionists: CFP OLA'2021 @ Sicilia Italy Message-ID: <20201014100805.Horde.6GS3M_ph4B9fhrHl8nKBbkA@mbox.dmi.unict.it> Apologies for cross-posting. Appreciate if you can distribute this CFP to your network. **************************************************************************************** OLA'2021 International Conference on Optimization and Learning 21-23 June 2021 Catania (Sicilia), Italy http://ola2021.sciencesconf.org/ **************************************************************************************** OLA is a conference focusing on the future challenges of optimization and learning methods and their applications. The conference OLA'2021 will provide an opportunity to the international research community in optimization and learning to discuss recent research results and to develop new ideas and collaborations in a friendly and relaxed atmosphere. OLA'2021 welcomes presentations that cover any aspects of optimization and learning research such as big optimization and learning, optimization for learning, learning for optimization, optimization and learning under uncertainty, deep learning, new high-impact applications, parameter tuning, 4th industrial revolution, computer vision, hybridization issues, optimization-simulation, meta-modeling, high-performance computing, parallel and distributed optimization and learning, surrogate modeling, multi-objective optimization ... Submission papers: We will accept two different types of submissions: - S1: Extended abstracts of work-in-progress and position papers of a maximum of 3 pages - S2: Original research contributions of a maximum of 10 pages Important dates: =============== Invited session organization Dec 18, 2020 Paper submission deadline Dec 18, 2020 Notification of acceptance March 24, 2021 Proceedings: Accepted papers in categories S1 and S2 will be published in the proceedings. A SCOPUS and DBLP indexed Springer book will be published for best accepted long papers. All proceedings will be available at the conference. From tomas.hromadka at gmail.com Wed Oct 14 15:44:30 2020 From: tomas.hromadka at gmail.com (Tomas Hromadka) Date: Wed, 14 Oct 2020 21:44:30 +0200 Subject: Connectionists: COSYNE 2021: Abstract submission is now open Message-ID: <5b86d17a-1ad4-945e-15db-e43b37f44451@gmail.com> ==================================================== Computational and Systems Neuroscience 2021 (Cosyne) MAIN MEETING ONLINE 24 - 26 February 2021 www.cosyne.org ==================================================== IMPORTANT DATES Abstract submission is now open Abstract submission deadline: 12 November 2020 ---------------------------------------------------- MEETING ANNOUNCEMENT ---------------------------------------------------- The annual Cosyne meeting provides an inclusive forum for the exchange of empirical and theoretical approaches to problems in systems neuroscience, in order to understand how neural systems function. Cosyne 2021 will take place online, February 24 - 26, 2021. Please note that the dates have changed slightly from the initial announcement. The goal of this year?s meeting is to promote early stage investigators. Therefore, there are no invited talks from established researchers. The format will include featured contributed talks chosen from submitted abstracts, and interactive poster-like presentations (short recorded presentation + live interactions). More details to follow. All abstract submissions will be reviewed as in previous years, but reviewing will be fully double blind. The deadline for Abstract submission will be November 12, 2020. Cosyne topics include but are not limited to: neural basis of behavior, sensory and motor systems, circuitry, learning, neural coding, natural scene statistics, dendritic computation, neural basis of persistent activity, nonlinear receptive field mapping, representations of time and sequence, reward systems, decision-making, synaptic plasticity, map formation and plasticity, population coding, attention, and computation with spiking networks. When preparing an abstract, authors should be aware that not all abstracts can be accepted for the meeting. Abstracts will be selected based on the clarity with which they convey the substance, significance, and originality of the work to be presented. ---------------------------------------------------- COSYNE 2021 TUTORIAL ---------------------------------------------------- Cosyne 2021 main meeting will be preceded by an online Cosyne Tutorial Session led by Kanaka Rajan (Icahn School of Medicine at Mount Sinai) on 23 February 2021. More details will be posted on www.cosyne.org. ORGANIZING COMMITTEE General & Program Chairs: Anne-Marie Oswald (U Pittsburgh) and Srdjan Ostojic (Ecole Normale Superieure Paris) Diversity Chairs: Eva Dyer (Georgia Tech, Emory) and Eric Shea-Brown (U Washington) Publicity Chair: Adam Calhoun (Princeton) Tutorial Chair: Il Memming Park (Stony Brook) Development Chair: Michael Long (NYU) EXECUTIVE COMMITTEE Stephanie Palmer (U Chicago) Zachary Mainen (Champalimaud) Alexandre Pouget (U Geneva) Anthony Zador (CSHL) PROGRAM COMMITTEE Athena Akrami (UCL) Demba Ba (Harvard) Omri Barak (Technion) Brice Bathellier (Paris) Yoram Burak (Hebrew University) Christine Constantinople (NYU) Saskia De Vries (Allen Institute) Victor de Lafuente (UNAM Mexico) Jan Drugowitsch (Harvard) Tatiana Engel (CSHL) Annegret Falkner (Princeton) Kevin Franks (Duke) Tim Hanks (UC Davis) Ann Hermundstad (Janelia) Andrew Leifer (Princeton) Sukbin Lim (Shanghai) Scott Linderman (Stanford) Mackenzie Mathis (EPFL Lausanne) Ida Momennejad (Microsoft) Cris Niell (U Oregon) Il Memming Park (Stony Brook) Adrien Peyrache (McGill Montreal) Kanaka Rajan (Icahn School of Medicine at Mount Sinai) Robert Rosenbaum (Notre Dame) Christina Savin (NYU) Marshal Shuler (Johns Hopkins) Daniela Vallentin (Max Planck Munich) CONTACT meeting [at] cosyne.org COSYNE MAILING LISTS Please consider adding yourself to Cosyne mailing lists (groups) to receive email updates with various Cosyne-related information and join in helpful discussions. See Cosyne.org -> Mailing lists for details. From iturria.medina at gmail.com Wed Oct 14 14:37:25 2020 From: iturria.medina at gmail.com (Yasser Iturria Medina) Date: Wed, 14 Oct 2020 14:37:25 -0400 Subject: Connectionists: Three-years funded Postdoctoral Fellow in Multiscale Mechanisms in Alzheimer's Disease Message-ID: *Postdoctoral Researcher in Molecular and Brain Macroscopic Mechanisms in Alzheimer's Disease* We are looking for a highly motivated postdoctoral researcher, for joining the *Neuroinformatics for Personalized Medicine* lab (NeuroPM ) at the Montreal Neurological Institute (McGill University, Montreal, Canada). The postdoc will be under the primary supervision of Prof. Yasser Iturria-Medina and will collaborate with multiple associated groups, including the McGill Center for Studies in Aging , CERVO - Laval Univ. , Lady Davis Research Institute , Yale Child Study Center and Litwin Family Centre in Genetic Medicine . The project, initially funded for 3 years and potentially extendable, includes the analysis of molecular and macroscopic brain alterations in AD, with a particular interest on characterizing disease evolution with novel computational techniques. For examples, see our recent publications: https://doi.org/10.1093/brain/awz400 and doi.org/10.1016/j.neuroimage.2018.06.028 The NeuroPM lab (http://www.neuropm-lab.com/) is affiliated with the Healthy brain for Healthy Lives (HBHL) initiative (*https://www.mcgill.ca/hbhl/ *), the Ludmer Center (http://ludmercentre.ca/), and the McConnell Brain Imaging Center (https://www.mcgill.ca/bic/), involving computationally intensive and interdisciplinary research on the brain. The MNI is an internationally renowned institution, characterized by the integration of research and patient care. Interested candidates should have a solid background and multiple publications in genetics and brain imaging in neurodegeneration. Experience in brain computational modeling will be an asset. Interested persons should send their CV and two reference contacts. *Contact*: Yasser Iturria Medina, Email: yasser.iturriamedina at mcgill.ca -- Yasser Iturria Medina, PhD. Assistant Professor of Neurology Canada Research Chair in Multimodal Data Integration in Neurodegeneration Neuroinformatics for Personalized Medicine lab (http://www.neuropm-lab.com/) Montreal Neurological Institute, McGill University Montreal, Canada H3A 2B4, Phone # 514-398-1524 -------------- next part -------------- An HTML attachment was scrubbed... URL: From joerg.luecke at uni-oldenburg.de Wed Oct 14 15:59:05 2020 From: joerg.luecke at uni-oldenburg.de (=?UTF-8?B?SsO2cmcgTMO8Y2tl?=) Date: Wed, 14 Oct 2020 21:59:05 +0200 Subject: Connectionists: Positions in Probabilistic Data Science / Machine Learning Lab, Oldenburg University, Germany In-Reply-To: <857f7b57-342b-4f4e-ab7f-81e2647bf036@uni-oldenburg.de> References: <857f7b57-342b-4f4e-ab7f-81e2647bf036@uni-oldenburg.de> Message-ID: <3d4ed379-9ebe-212f-f17b-b465e8ce3b3e@uni-oldenburg.de> Dear list, The Machine Learning Lab at the University of Oldenburg, Germany, is seeking to fill the position of a Researcher in Probabilistic Data Science. We look for somebody who has already obtained a PhD degree or is close to obtaining one. The only definitive source of information is here: https://uol.de/stellen/?stelle=67593 The application deadline is Oct 20 but we very likely also accept applications until the end of next week. We are seeking somebody with knowledge on probabilistic generative modeling. Best wishes, J?rg L?cke -- J?rg L?cke (PhD) Professor and Head of the Machine Learning Lab Department of Medical Physics and Acoustics School of Medicine and Health Sciences University of Oldenburg 26111 Oldenburg Germany www.uol.de/ml From jonizhong at msn.com Thu Oct 15 02:47:26 2020 From: jonizhong at msn.com (Joni Zhong) Date: Thu, 15 Oct 2020 06:47:26 +0000 Subject: Connectionists: [CFP] Special Issue on Human-in-the-loop Machine Learning and its Applications - NCAA Journal Message-ID: https://www.springer.com/journal/521/updates/17925472 ================================================================================= Call for Papers: NCAA Special Issue on human-in-the-loop machine learning and its applications ================================================================================= Deadline for submission: Dec 31, 2020 [https://media.springernature.com/w92/springer-static/cover/journal/521.jpg] Neural Computing and Applications | Topical collection on human-in-the-loop machine learning and its applications - Springer Topical Collection on Human-in-the-loop Machine Learning and its Applications. Aims, Scope and Objective. Human-in-the-Loop (HIL) means including human feedback into ... www.springer.com Dear Colleagues, Human-in-the-Loop (HIL) means including human feedback into the training loop of the machine learning models in order to facilitate the following requirements: 1) to improve the quality of training and reduce/prevent the error of the model. When the testing error is larger than a certain threshold, the HIL learning model is able to obtain the new data-points from the users in an interactive way. In some situations, a large error produced by the model should be avoided. For instance, reinforcement learning alone is not sufficient to achieve safety if there exists an exploration policy in robot manipulation, by which some unexpected actions may be generated. In such scenarios, the data-points from human guidance are crucial during both robot?s safe execution as well as model optimization. 2) to incorporate the human user labelling to improve the pre-trained models. During the training of the state-of-the-art models, the quality of the training data-sets is extremely important. One solution to actively incorporate more data is optimizing the models by including the human users? feedback (e.g. rewards in RL) or new data points (e.g. supervised learning) to adapt the pre-trained models in different environments. This special issue will also offer the opportunity for researchers and practitioners in the diverse fields of robotics to showcase its solutions and applications where human reinforcement feedback would have a positive impact on the training processes. The inclusion of HIL would allow robots and machine learning models to use both internal and external feedback to speed up the learning process and also improve its performance. In many ways this could allow the models to learn through their own self-reflection as well as the external input from a human. Specifically, as a following-up journal publication of the special session in HIL machine learning in IEEE SMC 2020, the extended versions of the accepted paper are mostly welcomed. Topics of interest include, but are not limited to: Human Guided Reinforcement Learning Human-robot Collaboration Human-robot Social Interaction Dialogue Systems with Human-in-the-loop Interpretable Machine Learning with Human-in-the-loop Active Learning and Continuous Learning Learning by Demonstration Human Factors in HCI/HRI etc. Deadlines Deadline for submissions: 31st December 2020 Deadline for review: 28th February 2021 Decisions: 20th March 2021 Deadline for revised version by authors: 20th April 2021 Deadline for 2nd review: 10th May 2021 Final decisions: 20th May 2021 Guest Editors Dr. Joni Zhong (Lead Guest Editor), Nottingham Trent University, UK, joni.zhong at ieee.org Dr. Mark Elshaw, Coventry University, UK, mark.elshaw at coventry.ac.uk Dr. Yanan Li, Sussex University, UK, yl557 at sussex.ac.uk Prof. Dr. Stefan Wermter, University of Hamburg, Germany, wermter at informatik.uni-hamburg.de Prof. Xiaofeng Liu, Hohai University, China, xfliu at hhu.edu.cn -------------- next part -------------- An HTML attachment was scrubbed... URL: From Jakob.Macke at uni-tuebingen.de Thu Oct 15 05:15:07 2020 From: Jakob.Macke at uni-tuebingen.de (Jakob Macke) Date: Thu, 15 Oct 2020 11:15:07 +0200 Subject: Connectionists: =?utf-8?q?PhD/Postdoc_position_in_T=C3=BCbingen?= =?utf-8?q?=2C_Deep_nets_+_human_neurophysiology_data?= Message-ID: <78A90B50-515D-49A6-B092-0947265555A3@uni-tuebingen.de> Dear colleagues, We have a position for a Ph.D. Student or Postdoctoral Researcher (m/f/d, E13 TV-L) in `Deep learning for studying population codes in the human brain?, starting as soon as possible. The initial fixed-term contract will be for 3 years with possible extension. Details at https://uni-tuebingen.de/en/196976. How do neural circuits in the human brain recognize objects, persons and actions from complex visual stimuli? To address these questions, we will develop deep convolutional neural networks for modelling how neurons in high-level human brain areas respond to complex visual information. We will make use of a unique dataset of neurophysiological recordings of single-unit activity and field potentials recorded from the medial temporal lobe of epilepsy patients. Our tools will open up avenues for a range of new investigations in cognitive and clinical neuroscience, and may inspire new artificial vision systems. The position is part of the BMBF-funded project DeepHumanVision in collaboration with the `Dynamic Vision and Learning? Group at TU Munich (Prof. Dr. Laura Leal-Taix?) and the Cognitive and Clinical Neurophysiology Group at University Hospital Bonn (Prof. Dr. Dr. Mormann). Our group develop computational methods that help scientists interpret empirical data, with a focus on basic and clinical neuroscience research. We want to understand how neuronal networks in the brain process sensory information and control intelligent behaviour, and use this knowledge to develop methods for the diagnosis and therapy of neuronal dysfunction. We aim to work in an interdisciplinary, collaborative and supportive work environment which emphasizes diversity and inclusion. T?bingen has an internationally renowned research community in artificial intelligence, machine learning and computational neuroscience, including the Cyber Valley Initiative, the T?bingen AI Center, the Excellence Cluster Machine Learning, and the new MSc Program Machine Learning. We are situated in the AI Research Building, in close proximity to the Max Planck Institutes for Intelligent Systems and Biological Cybernetics, and participate in the two International Max Planck Research Schools (IMPRS) `Intelligent Systems? and `Mechanisms of Mental Function and Dysfunction?. The position is open to candidates who have a PhD or Master?s in in a quantitative discipline (e.g. computer science, maths, statistics, physics, electrical engineering, computational neuroscience), a genuine interest in interdisciplinary work at the interface of machine learning and neuroscience, and strong programming skills (ideally Python/PyTorch). Prior experience in deep learning, and/or in analysing neurophysiological data with statistical methods is advantageous. The University seeks to raise the number of women in research and teaching and therefore urges qualified women academics to apply for these positions. Equally qualified applicants with disabilities will be given preference. The employment will be carried out by the central administration of the University of T?bingen. PhD applicants are also expected to apply to the IMPRS `Intelligent Systems? https://imprs.is.mpg.de, Deadline also November 2. Please submit your application materials to mls-sekretariat at inf.uni-tuebingen.de, with subject `Application: Postdoc/PhD DeepHumanVision?. Please include a CV, a brief statement of research interests, contact details of two referees and a work sample - anything that is genuinely your own work, e.g. a thesis, computer code, a research manuscript, an essay, or a publication. For postdoc applicants, we expect relevant prior publications. Application deadline: November 02, 2020. Best, Jakob Macke Prof. Dr. Jakob Macke Chair of Machine Learning in Science Excellence Cluster `Machine Learning: New Perspectives for Science? Department of Computer Science University of T?bingen Adjunct Senior Research Scientist, Department of Empirical Inference Max Planck Institute for Intelligent Systems T?bingen Jakob.Macke at uni-tuebingen.de Office: Franziska Weiler, mls-sekretariat at inf.uni-tuebingen.de www.mackelab.org/tuebingen From marcin at amu.edu.pl Thu Oct 15 07:27:23 2020 From: marcin at amu.edu.pl (Marcin Paprzycki) Date: Thu, 15 Oct 2020 13:27:23 +0200 Subject: Connectionists: Call for Papers - ICTAS2021 International IEEE conference-Durban, South Africa EXTENSION to 31 OCT In-Reply-To: <147b7223-0573-b2c9-94a1-bfef165ba96e@ibspan.waw.pl> References: <147b7223-0573-b2c9-94a1-bfef165ba96e@ibspan.waw.pl> Message-ID: Hello let us (e?)meet in Durban Best, Marcin Paprzycki &&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&& Dear Colleagues *The submission date for papers has been extended to 31 October 2020.* *Do take advantage of this great opportunity to showcase the work you have done using ICT especially during the COVID-19 pandemic. ?We look forward to your submissions.* Our e*xtremely successful *conference will be running again in 2021, please have a look on the website www.ictas.org. We would like to request your participation in our fourth annual Conference on Information Communications Technology and Society (ICTAS) to be held in Durban, South Africa on March 10 and 11, 2021 at the Blue Waters Hotel along the beautiful Durban beachfront. This conference has a *track record of 4 years* and every single paper presented at the past 4 conferences have been published in IEEE Xplore, making them eligible for DHET subsidy. Our conference is technically sponsored by IEEE and financially sponsored by the IEEE South Africa Computer Society. All papers will be double blind reviewed by at least two members of our international technical committee. All accepted and registered papers will be submitted to IEEE for potential inclusion into the IEEE Xplore digital library (ISBN: 978-1-7281-8081-6). Our conference is Scopus indexed and has a growing citation factor. Published papers will be eligible for DHET subsidy. *In the case of travel restrictions relating to the current COVID-19 pandemic, provisions will be made for virtual presentations.* Please feel free to *distribute the attached flyer to as many colleagues as possible*, we welcome all. Regards ICTAS committee -------------- next part -------------- A non-text attachment was scrubbed... Name: ICTAS Flyer3 Extended date.pdf Type: application/pdf Size: 145426 bytes Desc: not available URL: From fabio.bellavia at unifi.it Thu Oct 15 12:59:29 2020 From: fabio.bellavia at unifi.it (Fabio Bellavia) Date: Thu, 15 Oct 2020 18:59:29 +0200 Subject: Connectionists: [CfP] FAPER2020 - DEADLINE IS COMING! In-Reply-To: References: Message-ID: ???????????????????? FAPER2020 workshop at ICPR2020 ???????????? ---===== Apologies for cross-postings =====--- ?????????? Please distribute this call to interested parties _______________________________________________________________________ ?International Workshop on Fine Art Pattern Extraction and Recognition ????????????????????????? F A P E R?? 2 0 2 0 ??????????????????? workshop in conjunction with the ??? 25th International Conference on Pattern Recognition (ICPR2020) ???????????????????? Milan, Italy, January 11, 2021 ???????? >>> https://sites.google.com/view/faper-workshop/ <<< ? ? ? //??????? S U B M I S S I O N??? D E A D L I N E???????? \\ ?? ?? \\?? E X T E N D E D??? T O??? 1 7??? O C T O B E R !!!? // ?????? +++ UPDATES: the workshop will be taken FULLY VIRTUAL +++ ? *** PLEASE NOTE THAT PAPERS NOT ACCEPTED IN THE ICPR2020 GENERAL *** ?? ** SESSION AND FITTING FAPER2020 TOPICS COULD BE SUBMITTED HERE ** ??? -----> https://easychair.org/conferences/?conf=faper2020 <----- _______________________________________________________________________ === Aim & Scope === Cultural heritage, in particular fine art, has invaluable importance for the cultural, historic, and economic growth of our societies. Fine art is developed primarily for aesthetic purposes, and it is mainly concerned with paintings, sculptures, and architectures. In the last few years, due to technology improvements and drastically declining costs, a large-scale digitization effort has been made, leading to a growing availability of large digitized fine art collections. This availability, along with the recent advancements in pattern recognition and computer vision, has opened new opportunities for computer science researchers to assist the art community with automatic tools to analyse and further understand fine arts. Among the other benefits, a deeper understanding of fine arts has the potential to make them more accessible to a wider population, both in terms of fruition and creation, thus supporting the spread of culture. The ability to recognize meaningful patterns in fine art inherently falls within the domain of human perception, and this perception can be extremely hard to conceptualize. Thus, visual-related features, such as those automatically learned by deep learning models, can be the key to tackling problems of extracting useful representations from low-level colour and texture features. These representations can assist in various art-related tasks, ranging from object detection in paintings to artistic style categorization, useful for examples in museum and art gallery websites. The aim of the workshop is to provide an international forum for those who wish to present advancements in the state of the art, innovative research, ongoing projects, and academic and industrial reports on the application of visual pattern extraction and recognition for the better understanding and fruition of fine arts. The workshop solicits contributions from diverse areas such as pattern recognition, computer vision, artificial intelligence and image processing. === Topics === Topics of interest include, but are not limited to: - Application of machine learning and deep learning to cultural heritage - Computer vision and multimedia data - Generative adversarial networks for artistic data - Augmented and virtual reality for cultural heritage - 3D reconstruction of historical artifacts - Historical document analysis - Content-based retrieval in the art domain - Speech, audio and music analysis from historical archives - Digitally enriched museum visits - Smart interactive experiences in cultural sites - Projects, products or prototypes for cultural heritage restoration, preservation and fruition === Invited Speaker === Fabio Remondino (3DOM|FBK, Italy) Dr. Fabio Remondino is the head of the 3D Optical Metrology (http://3dom.fbk.eu) research unit at FBK - Bruno Kessler Foundation (http://www.fbk.eu), a public research center located in Trento, Italy. His main research interests are in the field of reality-based surveying and 3D modeling, sensor and data fusion and 3D data classification. He is working in all automation aspects of the entire 3D reconstruction pipeline for applications in the industrial, environmental and heritage field. He is author of more than 200 articles in journals and conferences. He is involved in knowledge and technology transfer, organizing more than 30 conferences, 20 summer schools and 5 tutorials. Fabio is currently serving as President of the ISPRS Technical Commission II (http://www.isprs.org) and Vice-President of EuroSDR (http://eurosdr.net). He was vice-President of CIPA Heritage Documentation (https://www.cipaheritagedocumentation.org/) from 2015 to 2019. === Important Dates === -? October? 17th 2020 - workshop submission deadline (*EXTENDED*) -? November 10th 2020 - author notification -? November 15th 2020 - camera-ready submission -? December? 1st 2020 - finalized workshop program === Submission Guidelines === Submissions must be formatted in accordance with the Springer's Computer Science Proceedings guidelines. The following paper categories are welcome: - Full papers (12-15 pages, including references) - Short papers? (6-8 pages, including references) Accepted manuscripts will be included in the ICPR 2020 Workshop Proceedings Springer volume. Once accepted, at least one author is expected to attend the event and orally present the paper. *** Due to the COVID pandemic, the workshop will be taken fully virtual. All accepted papers will be published. *** === FAPER 2020 Special Issue === Authors of selected papers will be invited to extend and improve their contributions in the Special Issue "Fine Art Pattern Extraction and Recognition" of the Journal of Imaging (MDPI). - https://www.mdpi.com/journal/jimaging/special_issues/faper2020 - === Organizing committee === Gennaro Vessio (University of Bari, Italy) Giovanna Castellano (University of Bari, Italy) Fabio Bellavia (University of Palermo, Italy) _________________________________________________________ ?Contacts: gennaro.vessio at uniba.it ?????????? giovanna.castellano at uniba.it ?????????? fabio.bellavia at unipa.it ?Workshop: https://sites.google.com/view/faper-workshop/ ?ICPR2020: https://www.micc.unifi.it/icpr2020/ From walter.senn at unibe.ch Thu Oct 15 10:00:21 2020 From: walter.senn at unibe.ch (Walter Senn) Date: Thu, 15 Oct 2020 16:00:21 +0200 Subject: Connectionists: Postdoc position on Biological Deep Learning References: <24F8C973-9ADA-43B3-8AF1-0CAA8A32EC0D@unibe.ch> Message-ID: Dear all One postdoc position devoted to learning in deep cortical networks is available in the Computational Neuroscience labs at the University of Bern, Switzerland. Our research is focussed on biologically realistic models of spatio-temporal processing in recurrent cortical networks and their relation to reinforcement learning, Bayesian computing, and neuromorphic implementations. The position is focussed on formalizing the dendritic processing of cortical pyramidal neurons, in particular on combining top-down and bottom-up information streams within pyramidal neurons, and in integrating these neurons in deep networks. The position is part of a collaboration with Profs Fritjof Helmchen and Giacomo Indiveri (UniZH / ETHZ) supported by the Swiss National Science Foundation and is available from January 1st, 2021, for 2 years (extendable). We offer a stimulating environment with three research groups in theoretical and computational neuroscience, along with experimental neuroscience at the same Department of Physiology (physio.unibe.ch/gruppen.aspx ), as well as close collaborations with other labs in neuroscience, artificial intelligence and neuromorphic engineering. Ideal candidates should have a strong background in computational neuroscience, machine learning, applied mathematics and/or physics. Please send your CV, publication list, letter of motivation and contact information for at least two references to Walter Senn (walter.senn at unibe.ch ) and Mihai Petrovici (mihai.petrovici at unibe.ch ), with cc to Virginie Sabado (virginie.sabado at unibe.ch ). The first evaluation round will begin on November 8, 2020. The positions will remain open until filled. With best regards, Mihai Petrovici and Walter Senn -------------- next part -------------- An HTML attachment was scrubbed... URL: From marieke.van.erp at dh.huc.knaw.nl Thu Oct 15 12:27:08 2020 From: marieke.van.erp at dh.huc.knaw.nl (Marieke van Erp) Date: Thu, 15 Oct 2020 16:27:08 +0000 Subject: Connectionists: Come work in Amsterdam! Two PhD positions in Amsterdam on 'Culturally aware AI' Message-ID: <0D473E4A-2655-4DCD-9D67-91BC98B1377C@dh.huc.knaw.nl> For the national research project ?AI:CULT - Culturally Aware AI,? funded by NWO, we are looking for two PhD Researchers, one at KNAW Humanities Cluster and one at Centrum Wiskunde & Informatica. About this vacancy The AI:CULT project will develop methods and techniques for applying AI to subjective and polyvocal data sets. The reasons for certain heritage data to be preserved, its interpretation throughout time, and the way heritage data is accessed after digitalisation is all subject to biases. The inherent richness, subjectivity and polyvocal nature of cultural heritage data limits and often even rules out the responsible use of AI. How do we model that ?Seventeenth Century? and ?The Golden Age? refer to the same era, yet are not fully synonymous and carry different semantic payloads? Current state-of-the-art AI cannot deal with subtleties in a way that does justice to the important role of the heritage institute as a trusted source of information. A crucial question is how can we reap the benefits of AI while guarding against its undesired consequences? AI:CULT addresses two case studies: 1) automatic analysis and enrichment of object-level descriptions and 2) the creation of data stories from raw collection data. Bias detection and filtering methods will be developed that will be directly tested on the heritage partners? workflows and made available to all memory organisations in the Netherlands. Job requirements For both positions we require: -Experience with (experimental) evaluation and statistical analyses; -Excellent English written and oral communication skills; -A keen interest in interdisciplinary research; -Ability and willingness to work in a team. Ph.D. student 1: Enriching Object-Level Collection Descriptions Affiliation: KNAW Humanities Cluster - DHLab Supervisors: Dr. Marieke van Erp and Prof. dr. Antal van den Bosch Candidates for this position should have a (research) master?s degree in artificial intelligence, computational linguistics, information sciences, data science, or comparable. In addition, you have strong computational skills, and an affinity with language technology and ideally knowledge representation and cultural heritage. Ph.D. student 2: Transparent Data Stories Affiliation: CWI - Human-centered Data Analysis Research Group Supervisors: Dr. Laura Hollink and dr. Jacco van Ossenbruggen Candidates for this position should have a (research) master?s degree in artificial intelligence, information science, data science, computer science or comparable. In addition, the ideal candidate has an affinity with one or more of the following fields: knowledge representation, cognitive science, computational linguistics. Strong computational skills will be necessary to design and implement algorithms and data pipelines and to run experiments. How to apply Applications for both positions can be sent by November 1st, 2020 to phdAICULT at bb.huc.knaw.nl using the subject heading ?PhD AI:CULT Project?. All applications should include a detailed resume, motivation letter, list of your MSc courses and grades, copy of your Master?s thesis and if applicable a list of publications. Please indicate which position you are applying for. Application for both positions is also possible. For residents outside the EER-area, a Toefl English language test might be required. For more information about the vacancy, please contact Dr. Marieke van Erp, marieke.van.erp at dh.huc.knaw.nl or Dr. Laura Hollink, l.hollink at cwi.nl. Collaboration Two PhD researchers will be hired on this project, one at each of the participating institutes. Although the PhD candidates will work on related but different sub-projects, a close collaboration between the PhD candidates is important for successful completion of the project. The PhD students are also expected to spend part of their time at the participating cultural heritage partners, the National Library of the Netherlands and the Netherlands Institute for Sound and Vision. The Humanities Cluster of the Royal Netherlands Academy of Arts and Sciences (KNAW) is a collaboration between three research institutes: the Huygens Institute for Dutch History, the International Institute for Social History (IISH) and the Meertens Institute for Dutch Language and Culture. The institutes are committed to groundbreaking research in the humanities, in which innovative (digital) methods play an important role. Centrum Wiskunde & Informatica (CWI) is the Dutch national research institute for mathematics and computer science and is part of the Institutes Organisation of the Dutch Research Council (NWO). The mission of CWI is to conduct pioneering research in mathematics and computer science, generating new knowledge in these fields and conveying it to trade, industry, and society at large. Furthermore, the AI:CULT is a project within the Cultural AI Lab (cultural-ai.nl), which studies, designs and develops socio-technological AI systems that are implicitly or explicitly aware of the subtle and subjective complexity of human culture. It is as much about using AI for understanding human culture as it is about using knowledge and expertise from the humanities to analyse and improve AI technology. It studies how to deal with input and output data in the context of the intended (or other) application areas, how to deal with cultural bias in data and technology and how to build AI technology that is optimised for cultural and ethical values. The different projects within the lab will interact and collaborate where possible, creating a community of researchers on the intersection of AI, cultural heritage and humanities. Terms of employment PhD Student 1 at KNAW HuC The initial labour agreement will be for a period of 12 months. After a positive evaluation, the agreement will be extended by 36 months. The gross monthly salary is ? 2.395,-- per month in the first year, rising to ? 3.061,-- in the fourth year, based on a fulltime appointment. The salary is supplemented with an 8% holiday allowance and an 8.3% end-of-year bonus. The Collective Labour Agreement for Dutch Universities is applicable. The Royal Academy of Science offers an attractive pension scheme, 6 weeks of holiday per year, the possibility to buy or sell holiday leave, as well as career development opportunities. Flexible hours and working from home are negotiable. Terms of employment PhD student 2 at Centrum Wiskunde & Informatica The terms of employment are in accordance with the Dutch Collective Labour Agreement for Research Centres ("CAO-onderzoeksinstellingen"). The initial labour agreement will be for a period of 18 months. After a positive evaluation, the agreement will be extended by 30 months. The gross monthly salary, for a PhD student on a full time basis, is ? 2.407,-- during the first year and increases to ? 3.085,-- over the four year period. Employees are also entitled to a holiday allowance of 8% of the gross annual salary and a year-end bonus of 8.33%. CWI offers attractive working conditions, including flexible scheduling and help with housing for expat employees. Please visit our website for more information about our terms of employment: https://www.cwi.nl/jobs/terms-of-employment Additional information The Humanities Cluster and CWI are equal opportunities employers. We encourage a diverse workforce: we endeavour to develop talent and creativity by bringing people from different backgrounds and cultures together. We recruit and select based on capabilities and talent. We strongly encourage everyone with the appropriate qualifications to apply for the vacancy, regardless of age, gender, origin, sexual orientation or physical abilities. This vacancy can also be found on: https://www.academictransfer.com/en/294810/two-phd-researchers-fulltime-one-at-knaw-humanities-cluster-and-one-at-centrum-wiskunde-informatica/ No recruitment agencies please. -- Digital Humanities Lab / dhlab.nl KNAW Humanities Cluster / huc.knaw.nl http://www.mariekevanerp.com -------------- next part -------------- An HTML attachment was scrubbed... URL: From markus.butz-ostendorf at biomax.com Thu Oct 15 11:51:57 2020 From: markus.butz-ostendorf at biomax.com (Markus Butz-Ostendorf) Date: Thu, 15 Oct 2020 17:51:57 +0200 Subject: Connectionists: Free Online Seminar: How to build your own Connectome? In-Reply-To: <76ed2081-8d59-d230-afcc-250505935c02@biomax.com> References: <76ed2081-8d59-d230-afcc-250505935c02@biomax.com> Message-ID: <5d0da1bb-6237-c434-b805-00cd4a43ddfb@biomax.com> Dear List, My apologies for cross-postings first of all! I would like to draw your attention to the first free online webinar on connectomics in clinical application with our novel neuroimaging software NICARA, particularly dedicated to human connectomics. More information below. With NICARA every neuroscientists can explore the beauty of connectomes and focus on connectome-related research questions without being a neuroimaging or neuroinformatics expert him- or herself. Register one of the limited NICARA demo accounts today via https://ssl.biomax.de/nicara/ Looking forward to meeting you online at the seminar! kind regards, Markus Can't read or see images? View this email in a browser Biomax Design Biomax Logo ** * *Save the Date:* *Free Online Seminar & Live Demo of NICARA* * ** NICARA Webinar With our neuroimaging solution *NICARA* we help clinicians working in the field of mental disorders to classify their patients faster and even better than ever before. Pharmacologists can significantly speed up the evaluation of the clinical efficacy of new drugs and scientists can access data and publications quickly and easily, thus greatly accelerating the success of research, while saving costs. All of these experts face more or less the same problem: Extracting structural and functional brain connectivity form raw images is time consuming and requires extensive expert knowledge. With *NICARA* you have thousands of publicly available connectomes at your fingertips and the possibility to analyze your own data by creating individual connectomes on the fly. Explore the world of connectomics with *NICARA* and learn how you can easily build your own Connectome. Register today for free for one of our upcoming Online Seminars and Live Demos. ?Online Seminar Date & Time (CET)? ?Free Registration ?for Clinicians ?20/10/2020, 3:00 pm ?Register here for Scientists? 10/11/2020, 3:00 pm? ??Register here for Pharmacologists? ?1/12/2020, 3:00 pm ??Register here To register, please click on one of the links above and request your access data via the webinar page. *We are looking forward to meeting you.* ** Biomax Banner Follow Us Biomax @ LinkedIn Biomax @ YouTube Biomax Informatics AG?Registered Office (Sitz der Gesellschaft): Planegg, Germany Court of Registration (Registergericht): AG M?nchen, HRB 134442 CEO (Vorstandsvorsitzender): Dr. Klaus Heumann Chairman of the Supervisory Board (Vorsitzender des Aufsichtsrats): Prof. Dr. Hans-Werner Mewes This email was sent by bettina.klitzing-stueckle at biomax.com to bettina.klitzing-stueckle at biomax.com Not interested? Unsubscribe | Update profile Biomax Informatics | Robert-Koch-Strasse 2 | 82152 Planegg | Germany Our Privacy Policy and Terms of Use. Additional Info -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: smime.p7s Type: application/pkcs7-signature Size: 4247 bytes Desc: S/MIME Cryptographic Signature URL: From nicholas.cummins at ieee.org Thu Oct 15 13:15:58 2020 From: nicholas.cummins at ieee.org (Nicholas Cummins) Date: Thu, 15 Oct 2020 18:15:58 +0100 Subject: Connectionists: ICMI 2020: Final Call for Participation Message-ID: ********************** ICMI2020: The 22nd ACM International Conference on Multimodal Interaction http://icmi.acm.org/2020/ 25-29 Oct 2020, Location: online ********************** UPDATE: Program is available http://icmi.acm.org/2020/index.php?id=program ********************** For full registration details and pricing see http://icmi.acm.org/2020/index.php?id=registration There is still time to register: Late registration deadline: 21 October 2020 Full conference - ACM/SIG Members: ?125, Non-members: ?150, Students: ?75 Workshops-only - ACM/SIG Members: ?75, Non-members: ?90, Students: ?50 ********************** Dear all, We kindly invite you to the 22nd ACM International Conference on Multimodal Interaction. ICMI is the premier international forum for multidisciplinary research on multimodal human-human and human-computer interaction, interfaces, and system development. The conference focuses on theoretical and empirical foundations, component technologies, and combined multimodal processing techniques that define the field of multimodal interaction analysis, interface design, and system development. We moved from an event initially to be held in a church in Utrecht, the Netherlands to an online event. The conference is fully packed with quality papers and we are very happy to be able to offer you the following events and speakers. Highlights include: Keynotes: - "From hands to brains: How does human body talk, think and interact in face-to-face language use?" by Prof.dr. Asli Ozyurek (Donders Institute for Brain, Cognition and Behavior, Radboud University) - "Deep Learning for Joint Vision and Language Understanding" by Prof.dr. Kate Saenko (Boston University, MIT-IBM Watson AI Lab) - "Sonic Interaction: From gesture to immersion" by Prof.dr. Atau Tanaka (Goldsmiths University of London) - "Human-centered Multimodal Machine Intelligence" by Prof.dr. Shrikanth (Shri) Narayanan (University of Southern California) Paper sessions: - More than 80 Long/short papers, more than 20 Late Breaking Reports, more than 10 Doctoral Consortium papers, 5 Demo papers, and more than 10 Grand Challenge papers Doctoral Consortium: - Twelve doctoral student papers, invited experts who will give feedback and advice doctoral students about their research Tutorial: - A tutorial will be given by Furhat Robotics Workshops: - Action Modelling for Interaction and Analysis in Smart Sports and Physical Education - Bridging social sciences and AI for understanding child behaviour - International Workshop on Deep Video Understanding - Face and Gesture Analysis for Health Informatics - Insights on Group & Team Dynamics - Modeling Socio-Emotional and Cognitive Processes from Multimodal Data in the Wild - Multisensory Approaches to Human-Food Interaction - Oral History and Technology - Multimodal Affect and Aesthetic Experience - Multimodal Interaction in Psychopathology - Multimodal e-Coaches - Social affective multimodal interaction for health - Multi-Timescale Sensitive Movement Technologies Grand Challenge: - Eighth Emotion Recognition in the Wild Challenge with thirteen Grand Challenge papers For a tentative global program and how we intend to organize the events and paper sessions, please check http://icmi.acm.org/2020/index.php?id=program. Come join ICMI2020 and meet us online 25-29 Oct 2020! Best, the organizing team of ICMI2020. -------------- next part -------------- An HTML attachment was scrubbed... URL: From jochem.rieger at uni-oldenburg.de Thu Oct 15 13:28:14 2020 From: jochem.rieger at uni-oldenburg.de (Jochem Rieger) Date: Thu, 15 Oct 2020 19:28:14 +0200 Subject: Connectionists: Post-doc position 3+2 years Open and reproducible Science. Deadline 21.10.2020 Message-ID: <072c7ad7-4047-133e-4e35-d32cc8153c0d@uni-oldenburg.de> Dear colleagues, We have an open post-doc position for 3+2 years at the Neuroimaging Unit of Uni Oldenburg for the development of tools and infrastructure? for open data data and reproducible science based on the BIDS standard. The position? complemented by a full time technician position for support. The initial duration is 3 years and can be extended by another 2 years. The announcement is below. We are looking forward to applications, ????? Jochem ---- The Neuroimaging Unit at the School of Medicine and Health Sciences of the Carl von Ossietzky Universit?t Oldenburg is seeking to fill the position of a *Postdoctoral Research Associate m/f/d *(Salary level E13 TVL, 100%) *for the development of acquisition, storage and processing pipelines for reproducible science building on the BIDS standard.* The position is embedded in a DFG Core Facility grant and is available*as soon as possible*for a duration of three years (with the possibility to extend another two years after successful project evaluation). The position is suitable for part-time work. In a newly funded project we aim to implement data storage and processing pipelines for reproducible science building on the BIDS standard. The Neuroimaging Unit hosts a state of the art MEG (Elekta Triux) and an MRI (Siemens Prisma 3T) and is embedded in an excellent interdisciplinary scientific environment with a strong research focus on neurosensory, neurocognitive, and medical research. The successful candidate is expected to actively contribute to the implementation of neuroscience data acquisition, storage, and reproducible analysis pipelines building on the BIDS standard at the University of Oldenburg, to contribute to community efforts, and dissemination. Therefore, candidates are expected to have an academic university degree (Master or equivalent) in the field of informatics, engineering, neuroscience or psychology and have shown their ability to perform excellent scientific work, demonstrated by the outstanding quality of their doctorate/PhD research and an excellent publication record. Prior experience with the BIDS standard as well as its programming, experience with neuroimaging techniques and data analysis (especially fMR or MEG/EEG) and fluency in English is required. Experience with open science tools and databases, other neurophysiological modalities, as well as knowledge of German are desirable. The University of Oldenburg is dedicated to increase the percentage of female employees in the field of science. Therefore, female candidates are strongly encouraged to apply. In accordance to ? 21 Section 3 NHG, female candidates with equal qualifications will be preferentially considered. Applicants with disabilities will be given preference in case of equal qualification. Please send your application including a cover letter, CV, list of potential referees, links to recent publications and copies of certificates for academic grades to Prof. Jochem Rieger, Department of Psychology, University of Oldenburg, 26111 Oldenburg, Germany; (jochem.rieger at uni-oldenburg.de ). Electronic applications (one pdf file) are preferred. For inquiries please use the same contact. The application deadline is*21st of October 2020*. -- Prof. Dr. rer. nat. Jochem Rieger Head of Applied Neurocognitive Psychology Head of Neuroimaging Unit Faculty VI Carl-von-Ossietzky University 26111 Oldenburg Germany Phone: +49(0)4417984533 Fax: +49(0)4417983865 -------------- next part -------------- An HTML attachment was scrubbed... URL: From ezio.bartocci at tuwien.ac.at Fri Oct 16 04:04:48 2020 From: ezio.bartocci at tuwien.ac.at (Ezio Bartocci) Date: Fri, 16 Oct 2020 10:04:48 +0200 Subject: Connectionists: (Deadline November 30 2020) - 10 PhD funded positions in SecInt Doctoral College at TU Wien on Secure and intelligent human-centric digital technologies Message-ID: <2AFD0428-2862-40A3-891E-87390687E312@tuwien.ac.at> We are looking for 10 brilliant students to hire with a very competitive salary (up to 29000 Euro/net per year) for four years. The students will be trained within a new PhD school (SecInt https://secint.visp.wien/ ) on secure and intelligent human-centric digital technologies. In our research group (TrustCPS ), I am looking for a candidate working on verifying and (ensuring at runtime) safety and security properties in autonomous cyber-physical systems such as self-driving cars. This particular position is co-funded by TU Wien and the Austrian Institute of Technology for 40 hours/per week (full-time) with a four years contract. The position will be co-supervised together with Dr. Dejan Nickovic (https://www.ait.ac.at/en/research-topics/dependable-systems-engineering/verification-validation/ ). The working language will be English. The link for the application is the following: (https://jobs.tuwien.ac.at/Job/136572?culture=en&fbclid=IwAR0QQB-iIlB2toQ8VscR_GdTbs5nWxs4EeR5mJqMuJE3v0W4NVmRNyRyHeA ) The deadline to apply is the end of November. Concerning the quality of life, Vienna has been ranked consecutively in the last ten years as the most livable place in the world by the international consulting agency Mercer: https://theculturetrip.com/europe/austria/articles/10-reasons-vienna-was-named-city-with-highest-quality-of-life/ The cost of life is very affordable and very low compared to other important metropolitan cities. The Faculty of Informatics at TU Wien is consistently ranked among the best top 100 in the world in several rankings. https://informatics.tuwien.ac.at/news/1868/documents/139 The research environment is incredibly vibrant with a critical mass of top scientists in computer science (not only at TU Wien, but also in several close research institutions such as for example IST Austria) with whom to collaborate. Furthermore, the PhD school gives also the possibility to visit abroad, to make internships and to collaborate with several other renown industrial (e.g. Amazon, Microsoft, etc) and academic partners (e.g., Stanford University, TU Munich, RWTH Aachen, etc.). Do not hesitate to contact me for further information. Best regards Ezio Bartocci -- Prof. Ezio Bartocci Faculty of Informatics TU Wien, Vienna University of Technology, Austria Treitlstra?e 3, 1040 Vienna, Austria E-Mail: ezio.bartocci at tuwien.ac.at Phone: +43 (1) 58801 - 18226 Website: http://www.eziobartocci.com DBLP: https://dblp.uni-trier.de/pid/b/EzioBartocci.html Scopus: https://www.scopus.com/authid/detail.uri?authorId=14053557900 -------------- next part -------------- An HTML attachment was scrubbed... URL: From Menno.VanZaanen at nwu.ac.za Fri Oct 16 04:34:28 2020 From: Menno.VanZaanen at nwu.ac.za (Menno Van Zaanen) Date: Fri, 16 Oct 2020 10:34:28 +0200 Subject: Connectionists: Vacancy: Computational Linguist at SADiLaR Message-ID: <5F895B14020000AE0038905E@v-pgw-nlx2.p.nwu.ac.za> The South African Centre for Digital Language Resources (SADiLaR) has a position available for a computational linguist. Full ad: https://www.sadilar.org/index.php/en/10-news/265-vacancies-cl-2020-10-15 The South African Centre for Digital Language Resources (SADiLaR), in conjunction with the North-West University (NWU), is offering a position for a computational linguist. This position is crucial for research and development in Digital Humanities (DH) and Human Language Technology (HLT) that form the essence of SADiLaR, which is a national centre supported by the Department of Science and Innovation (DSI). This Centre operates as a new research entity hosted by the North-West University and initiates and co-ordinates dedicated projects executed by the centre itself, as well as by the nodes comprising of the University of Pretoria, the University of South Africa, the CSIR, CTexT, as well as a partnership (ICELDA) of four South African Universities. Minimum Requirements * PhD in either Computational Linguistics, Natural Language Processing, General Linguistics, Human Language Technology, Digital Humanities, Computer Science, Information Technology, Communication Technology or Artificial Intelligence with a clear focus on computational aspects of linguistics. * Five years' applicable experience in the use of Python (recommended). Other programming languages used within the computational linguistics domain can also be considered. * Five years' experience in the use of different operating systems including Linux. * Experience as a supervisor/co-supervisor of postgraduate students. * Three years' experience in the publication of peer reviewed academic articles and research reports. HOW TO APPLY: http://nwu.pnet.co.za/index.php?s=advert_view&g=11080&x=6361614&i=3903&pop=1 CLOSING DATE: 30 October 2020 COMMENCEMENT OF DUTIES: As soon as possible ENQUIRIES: Prof Menno van Zaanen, Menno.vanZaanen at nwu.ac.za NWU CORONA VIRUS: http://www.nwu.ac.za/coronavirus/ Vrywaringsklousule / Disclaimer: http://www.nwu.ac.za/it/gov-man/disclaimer.html -------------- next part -------------- An HTML attachment was scrubbed... URL: From zoltan.szabo.list at zoho.com Fri Oct 16 15:19:57 2020 From: zoltan.szabo.list at zoho.com (Zoltan Szabo) Date: Fri, 16 Oct 2020 21:19:57 +0200 Subject: Connectionists: Data Science Summer School goes virtual & update: D-5 reminder Message-ID: <8f175b23-1405-c895-48b6-d74c50ee25c8@zoho.com> Dear All, This is a quick email about the Data Science Summer School (DS^3) organized by the Data Science Initiative of ?cole Polytechnique, the DATAIA Institute and the Chaire Stress Test. We changed the event to virtual for health/safety reasons (COVID), there will be an opportunity to join small-group (<=10-12) tutorials with practical sessions (on the 4-5th and 9th Jan), and updated the registration accordingly (fees and it is open now until Oct. 21). You are welcome to join: "https://www.ds3-datascience-polytechnique.fr"! Key dates: -Registration deadline: Oct. 21, 2020, -Notification of acceptance: Nov. 4, 2020. -Event: Jan. 4-9, 2021. Best, Zoltan, on behalf of the organizers From burcu.urgen at gmail.com Fri Oct 16 09:11:26 2020 From: burcu.urgen at gmail.com (=?UTF-8?Q?Burcu_Ay=C5=9Fen_=C3=9Crgen?=) Date: Fri, 16 Oct 2020 16:11:26 +0300 Subject: Connectionists: Tenure-track Positions at the Department of Psychology, Bilkent University Message-ID: *Open-Rank Positions at the Department of Psychology, Bilkent University* Bilkent University invites tenure-track faculty applications (rank open) in the Department of Psychology. The university?s strategic plan includes an expansion of the psychology department (psy.bilkent.edu.tr). Accordingly, we seek applications from promising or established scholars in all areas of psychology (social psychology, developmental psychology, cognitive psychology, experimental psychology, clinical psychology, and neuroscience). Those with interdisciplinary approaches to studying psychology that bridge different subfields and those offering a social, developmental, and/or clinical perspective are particularly encouraged to apply. The language of instruction is English. The Department and the Interdisciplinary Graduate Program in Neuroscience (neuro.bilkent.edu.tr) offer Master?s and PhD programs. For 5 consecutive years, each newly admitted Psychology major has scored in the top 6% or higher on the national university entrance exam. The Department has newly renovated research laboratories, as well as access to the university?s state-of-the-art facilities, which include a 3 Tesla MR scanner, animal research center, and EEG equipment. Bilkent is located in Ankara, Turkey?s metropolitan capital with daily direct flights to Istanbul and other major European cities. Bilkent University also provides faculty members and their families with free housing and access to private health insurance. *Qualifications and Responsibilities:* Applicants should have a PhD in psychology or a related discipline, and should have an excellent publication record (requirements vary with rank). A demonstrated ability or the potential to secure external research funding will be a strong advantage. Faculty members are expected to maintain productive research programs. Successful applicants will teach 2 courses per semester (with no teaching requirement during summers, and a possibility of reduced teaching in the first year of appointment), and supervise PhD, Master?s, and senior thesis students. *Appointment:* The full-time appointments will begin in September 2021 (negotiable). Salary will be internationally competitive and commensurate with qualifications and experience. *Application Procedure* Applicants should submit - a cover letter - CV - research statement - teaching statement - pdf copies of 3 representative publications; and - contact information for 3-5 professional references Review of applications will commence on November 29, 2020 and continue until the positions are filled. To apply please go to the following link: https://stars.bilkent.edu.tr/staffapp/PSYC2020 . For more information regarding the Psychology Department and Bilkent University, please visit the following websites: psy.bilkent.edu.tr neuro.bilkent.edu.tr feass.bilkent.edu.tr bilkent.edu.tr -- Burcu Ay?en ?rgen, PhD Assistant Professor Department of Psychology & Interdisciplinary Neuroscience Program Aysel Sabuncu Brain Research Center National Magnetic Resonance Research Center Bilkent University 06800, Bilkent, Ankara, Turkey Email: burcu.urgen at bilkent.edu.tr Website: http://burcu.urgen.bilkent.edu.tr Lab: http://www.ccn.bilkent.edu.tr Tel: +90 312 290 30 91 or +90 312 290 1807 -------------- next part -------------- An HTML attachment was scrubbed... URL: From gaute.einevoll at nmbu.no Sun Oct 18 10:40:14 2020 From: gaute.einevoll at nmbu.no (Gaute Einevoll) Date: Sun, 18 Oct 2020 14:40:14 +0000 Subject: Connectionists: PhD-positions in computational neuroscience at the University of Oslo as part of CompSci grant in EU Horizon 2020 Message-ID: CompSci is a Doctoral Programme launched and managed by the Faculty of Mathematics and Natural Sciences at the University of Oslo (UiO). It is partly funded by the EU Horizon 2020 under the Marie Sk?odowska-Curie Action (MSCA) - Co-funding of Regional, National and International Programmes (COFUND). The CompSci Doctoral Program will recruit 32 PhDs in two calls. In this Call, we open for applications to the 1st cohort of 16 PhD fellowship positions, that will join our PhD programme starting autumn 2021 at UiO. The possible PhD-projects span over a wide range of topics where methods from computational science are applied to different fields in the natural sciences: https://www.mn.uio.no/compsci/english/projects/ Four of the possible projects in Call 1 are within computational neuroscience: * Bio-inspired neural networks for navigation Supervisors: Anders Malthe-S?renssen, Gaute T. Einevoll * Large-scale recordings of neurons to reveal mechanisms of learning and memory Supervisors: Marianne Fyhn, Anders Malthe-S?renssen * Large-scale network simulations of mouse visual cortex Supervisors: Gaute T. Einevoll, Marianne Fyhn * Modelling systems levels changes in brain aging induced by genome instability Supervisors: Hilde Nilsen, Gaute T. Einevoll For information about how to apply, see https://www.jobbnorge.no/en/available-jobs/job/193610/compsci-call-1-marie-sklodowska-curie-phd-fellowships-in-natural-sciences-16-positions . The application deadline for Call 1 is: January 3rd 2021 Questions about the individual projects should be sent to the supervisors listed above. -------------- next part -------------- An HTML attachment was scrubbed... URL: From vcutsuridis at gmail.com Fri Oct 16 09:58:28 2020 From: vcutsuridis at gmail.com (Vassilis Cutsuridis) Date: Fri, 16 Oct 2020 14:58:28 +0100 Subject: Connectionists: Call for papers : Special Issue on Brain Simulation and Spiking Neural Networks ( Cognitive Computation - Springer) Message-ID: *Call For Papers:Journal : Cognitive ComputationSpecial Issue : Brain Simulation and Spiking Neural Networks* https://www.springer.com/journal/12559/updates/18336610 *Scope and Motivation* During the past 10 years, many experiments have been implemented with the aim of improving our understanding on the brain?s structure and function. Alongside, simulation neuroscience has become an important strategy to investigate how the brain works. The Human Connectome Project in the US started in 2009 and aimed to provide a big human brain mapping dataset on which many brain models have already been tested. In the Human Brain Project in the EU, a large-scale virtual rodent brain simulation is being built with the purpose of revealing various brain activities. In Japan, whole human-scale brain simulations on the Fugaku supercomputer are being established to investigate how neural networks develop their learning process. On the other hand, the foundation of cognitive computing and control mechanism can be revealed from the simulations of brain circuits and the neural dynamics. Moreover, these are also critical to improve current artificial intelligent systems and for building brain intelligence level algorithms. In this special issue, we invite researchers to present their state-of-the-art approaches, introduce recent advances and therefore show the potential of brain-simulation-related technologies. *Guest Editors* Jordi Sol?-Casals (jordi.sole at uvic.cat) Cesar F. Caiafa (ccaiafa at fi.uba.ar) Zhe Sun (zhe.sun.vk at riken.jp) Vassilis Cutsuridis (vcutsuridis at lincoln.ac.uk) *Topics* Topics include but are not limited to: ? Brain ?Connectivity mapping and functional mapping ? Data analysis methods for connectome data ? Multi-scale neural system simulation ? Neuromorphic hardware ? High-performance computing system for large scale simulations ? Neural system inspired spiking neural network ? Neuro-robotics systems ? Sensorimotor learning model *Deadlines* *Submissions Deadline*: *April 1, 2021* First notification of acceptance: June 1, 2021 Submission of revised papers: August 1, 2021 Final notification to the authors: Oct 1, 2021 Submission of final/camera-ready papers: Nov 1, 2021 Publication of special issue: Nov 22, 2021 *Submission Instruction:* Prepare your paper in accordance with the Journal guidelines: www.springer.com/12559. Submit manuscripts at: http://www.editorialmanager.com/cogn/. Select ?SI: Brain Simulation and Spiking Neural Networks? for the special issue under ?Additional Information.? Your paper must contain significant and original work that has not been published nor submitted to any journals. All papers will be reviewed following standard reviewing procedures of the Journal. *Author Resources* Authors are encouraged to submit high-quality, original work that has neither appeared in, nor is under consideration by other journals. All papers will be reviewed following standard reviewing procedures for the Journal. Papers must be prepared in accordance with the Journal guidelines: www.springer.com/12559 Springer provides a host of information about publishing in a Springer Journal on our Journal Author Resources page, including FAQs , Tutorials along with Help and Support. Other links include: - editorial policies - publication policies - copyright transfer - self-archiving - OA funding - open choice - funder compliance - read and publish agreements - preprint sharing - my publication process - production - publication - post-publication - ORCID - Publons - article sharing - citation alerts If you have additional questions, please do not hesitate to contact us. Best regards, Vassilis --- Dr Vassilis Cutsuridis Senior Lecturer School of Computer Science & Lincoln Sleep Research Center University of Lincoln Lincoln UK Tel: +44 (0) 1522 83 5701 Email: vcutsuridis at lincoln.ac.uk Web: http://staff.lincoln.ac.uk/vcutsuridis Personal website: http://www.vassiliscutsuridis.org/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From steve at bu.edu Sat Oct 17 16:37:46 2020 From: steve at bu.edu (Grossberg, Stephen) Date: Sat, 17 Oct 2020 20:37:46 +0000 Subject: Connectionists: Lecture video about Explainable and Reliable AI: Deep Learning and Adaptive Resonance In-Reply-To: References: , , Message-ID: Dear Colleagues, On September 19, I gave a pre-recorded keynote lecture on Zoom to the 13th International Conference on Brain Informatics about Explainable and Reliable AI, a topic that's of considerable interest these days. The lecture's title and url are: Explainable and Reliable AI and Autonomous Adaptive Intelligence: Deep Learning, Adaptive Resonance, and Models of Perception, Emotion, and Action http://sites.bu.edu/steveg/files/2020/10/Grossberg-keynote-for-BI-on-9-19-20.mp4 The lecture can also be found on my web page sites.bu.edu/steveg along with a pdf of its powerpoint slides and various other lectures and articles. Best, Steve Grossberg Stephen Grossberg http://en.wikipedia.org/wiki/Stephen_Grossberg http://scholar.google.com/citations?user=3BIV70wAAAAJ&hl=en https://youtu.be/9n5AnvFur7I https://www.youtube.com/watch?v=_hBye6JQCh4 Wang Professor of Cognitive and Neural Systems Director, Center for Adaptive Systems Professor Emeritus of Mathematics & Statistics, Psychological & Brain Sciences, and Biomedical Engineering Boston University sites.bu.edu/steveg steve at bu.edu -------------- next part -------------- An HTML attachment was scrubbed... URL: From Donald.Adjeroh at mail.wvu.edu Sun Oct 18 11:06:26 2020 From: Donald.Adjeroh at mail.wvu.edu (Donald Adjeroh) Date: Sun, 18 Oct 2020 15:06:26 +0000 Subject: Connectionists: SBP-BRiMS'2020 -- Conference starts tomorrow !!! Barry G. Silverman to Keynote ... In-Reply-To: References: , , , , , , , , , , , , , , , , , , , , , , Message-ID: Apologies if you receive multiple copies The SBP-BRiMS 2020 conference starts tomorrow, Oct 19, 2020. Registration is still open. http://sbp-brims.org/2020/registration/ Our Keynote Speaker is Professor Barry G. Silverman https://www.seas.upenn.edu/~barryg/ More details below ... Conference Registration: Registration is now open for the 2020 International Conference on Social Computing, Behavioral-Cultural Modeling & Prediction and Behavior Representation in Modeling and Simulation (SBP-BRiMS), Oct. 18-21, 2020. Conference format is virtual/online. You can register at the website: http://sbp-brims.org/2020/registration/ Conference Fellowships: A limited number of fellowships is available for students and members of underrepresented groups to support participation in the conference. Please apply early as the slots are limited. For more details, visit the conference website http://sbp-brims.org/ , and check the menu for Scholarships, under "Conference Information". Keynote: Barry G. Silverman, PhD Professor Emeritus, Electrical and Systems Engineering, University of Pennsylvania https://www.seas.upenn.edu/~barryg/ Topic: StateSim: A Country Modeling and Systems Engineering Journey For more details, see the website: http://sbp-brims.org/2020/keynote/ Two New Special Tracks: Validation Track: For details, see the CFP at the conference website: http://sbp-brims.org/ COVID-19 Pandemic Track: For details, see the CFP at the conference website: http://sbp-brims.org/ Special Issues : Special issues are planned for selected papers from the main conference, and for the COVID-19 special track. Deadline for submission for Journal Special Issues: Nov. 15, 2020 SBP-BRiMS 2020 Oct. 19 - 21| Online/virtual www.sbp-brims.org Connect with #sbpbrims on social: Follow us on Twitter: http://twitter.com/sbpbrims Like us on Facebook: http://facebook.com/sbpbrims Follow us on LinkedIn: https://www.linkedin.com/company/sbpbrims/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From timvogels at gmail.com Fri Oct 16 19:45:06 2020 From: timvogels at gmail.com (Tim Vogels) Date: Sat, 17 Oct 2020 01:45:06 +0200 Subject: Connectionists: How to find your scientific neighbours, future colleagues Message-ID: Dear Colleagues, For those of you who are looking for a position as a postdoc (or faculty), consider posting your info to world-wide.org/neighbors . It's a place to find your closest scientific neighbours, and maybe your next position. Fill in & submit your info, and a few minutes later we will post it, if you want to with the best matching labs. /neighbors is an extension of the popular worldwideneuro.com , and currently works best for neuroscience matches. For those of you who are looking for postdocs and advertising positions for postdocs to HIRE, it may be interesting to also post your ads on world-wide.org/neighbors . Posting your ad to the website will make it visible for a much longer time than a single fleeting email. And while you are here, come brows through the info on people looking for jobs. Finally, you can also just browse if you're just ?curious?, and check out who your closest neighbours are. Or find some amazing talks on worldwideneuro.com or https://www.world-wide.org/Physics-of-Life/ If you want to, let us know if you like it, and what improvements you?d like to see. All the best, (Panos Bozelos and ) Tim Vogels ------------- Vogelslab.org IST, Austria -------------- next part -------------- An HTML attachment was scrubbed... URL: From michal.rafal.zareba at gmail.com Mon Oct 19 09:14:33 2020 From: michal.rafal.zareba at gmail.com (=?UTF-8?B?TWljaGHFgiBaYXLEmWJh?=) Date: Mon, 19 Oct 2020 15:14:33 +0200 Subject: Connectionists: NEURONUS 2020 IBRO Neuroscience Forum (8-11 December 2020, ONLINE) Message-ID: *REGISTRATION for NEURONUS 2020 IBRO Neuroscience Forum is open only UNTIL OCTOBER 31! The fee has been lowered to 12?. The number of the participants is limited only to 1000 ? hurry up! More information and registration forms can be found on our website: **http://neuronusforum.pl/* *.* With prominent speakers and an unique atmosphere of Krakow, one of the oldest and most beautiful Polish cities, NEURONUS IBRO Neuroscience Forums have established themselves in the European calendar of scientific events as a platform for communication between scientists from different fields of neuroscience. Unfortunately, the ongoing COVID-19 pandemic has forced us to move our event to the virtual plane. The program of the conference consists of numerous sessions on biological, cognitive, computational and medical aspects of neuroscience, creating a dynamic environment for sharing knowledge. The schedule of the meeting is further complemented with lectures by invited guests, and we invest a lot of effort to attract as influential neuroscientists as possible. This year?s keynote speakers include: - *Karl Friston *(University College London, the UK) - *Pico Caroni *(University of Basel, Switzerland) - *Karin Roelofs *(Radboud University Nijmegen, the Netherlands) - *Alejandro Schinder *(Leloir Institute, Buenos Aires, Argentina) - *Adam Hampshire *(Imperial College London, the UK) - *Dayu Lin *(New York University School of Medicine, the USA) Furthermore, a special panel concerning the Future of Neuroscience will be held. We have confirmed participation of three pioneering researchers: - *Viktor Jirsa *(Aix-Marseille University, France) - *Panayiota Poirazi* (Institute of Molecular Biology and Biotechnology, Heraklion, Greece) - *Dominik Paquet *(Ludwig Maximilian University of Munich, Germany) During the upcoming 11th edition of the conference, we will traditionally continue to put *emphasis on development of early-career researchers*. The main purpose of this event is to provide means for both young and experienced neuroscientists to share the latest discoveries, knowledge and experience in neuroscience, as well as make valuable contacts with scientists representing various fields of neurobiology. We actively promote young scientists through preferentially allocating oral presentations of their experimental results. We strongly encourage you to join this special initiative, and hope to see you soon! On behalf of the Organising Committee, Micha? Zar?ba -------------- next part -------------- An HTML attachment was scrubbed... URL: From plan4act at phys.uni-goettingen.de Tue Oct 20 03:14:01 2020 From: plan4act at phys.uni-goettingen.de (DPI, plan4act) Date: Tue, 20 Oct 2020 07:14:01 +0000 Subject: Connectionists: Online workshop series - Neural Control: From data to machines Message-ID: <3eaf7473fcbe4fd4bc49fcd30ef5a842@phys.uni-goettingen.de> We are pleased to announce the online workshop series Neural Control: From data to machines with weekly Zoom-sessions starting on November 5th, 2020. Topic: Movement disorders leave individuals unable to control parts of their bodies, creating a disconnect between their brain and the world around them. This workshop series looks at how neural activity can be mapped to control smart systems, producing desired movements on demand. To discuss the implied problems and solutions, we have brought together experts from the different involved scientific fields. Details and registration at: https://alexandria.physik3.uni-goettingen.de/cns-group/projects/webinars/ Confirmed Speakers: * Dario Farina * Silvestro Micera * Tonio Ball * Nick Ramsay * Juan ?lvaro Gallego * Florentin W?rg?tter * Alexander Gail * Christian Tetzlaff * Michael Fauth * Tomoki Fukai * Petra Ritter * Valerio Mante * Hans Scherberger * Gordon Cheng * Poramate Manoonpong * Jan-Matthias Braun * Eugenio Gaeta * Daniel Durstewitz * Yukie Nagai Please forward to anyone who may be interested. Best, Florentin W?rg?tter and Christian Tetzlaff -------------- next part -------------- An HTML attachment was scrubbed... URL: From marcello.pelillo at gmail.com Tue Oct 20 07:28:10 2020 From: marcello.pelillo at gmail.com (Marcello Pelillo) Date: Tue, 20 Oct 2020 13:28:10 +0200 Subject: Connectionists: Frontiers in Computer Vision (open access) Message-ID: The *Computer Vision* section of *Frontiers in Computer Science* (formerly "Computer Vision and Image Analysis") is undergoing a massive overhaul in terms of scope, editorial board, and editorial strategies: https://www.frontiersin.org/journals/computer-science/sections/computer-vision We welcome contributions in all relevant areas of computer vision, from both academia and industry. We also particularly welcome Special Issue proposals ("Research Topics" in Frontiers' terminology) on cutting-edge themes: https://www.frontiersin.org/about/research-topics Among the distinguishing features of Frontiers' open-access journals are fast publication time and an innovative collaborative peer-review process (see here for details). If you have any questions about the journal feel free to contact me. Best regards -mp -- Marcello Pelillo, *FIEEE, FIAPR* Professor of Computer Science Ca' Foscari University of Venice, Italy Specialty Chief Editor, *Computer Vision - Frontiers in Computer Science* -------------- next part -------------- An HTML attachment was scrubbed... URL: From fabio.bellavia at unifi.it Tue Oct 20 09:22:05 2020 From: fabio.bellavia at unifi.it (Fabio Bellavia) Date: Tue, 20 Oct 2020 15:22:05 +0200 Subject: Connectionists: [CFP] MAES workshop at ICPR2020 - DEADLINE IS COMING! Message-ID: ???????????????????? MAES2020 workshop at ICPR2020 ?????????? ---===== Apologies for multiple posting =====--- ?????????? Please distribute this call to interested parties _______________________________________________________________________ ??? Machine Learning Advances Environmental Science (MAES at ICPR2020) ??????????????????????????? workshop at the ??? 25th International Conference on Pattern Recognition (ICPR2020) ???????????????????? Milan, Italy, January 10, 2021 ????????? >>> https://sites.google.com/view/maes-icpr2020/ <<< ?? ? //????????? S U B M I S S I O N??? D E A D L I N E????????? \\ ?? ? \\?? E X T E N D E D??? T O??? 2 5??? O C T O B E R !!!???? // ?????? +++ UPDATES: the workshop will be taken FULLY VIRTUAL +++ ? *** PLEASE NOTE THAT PAPERS NOT ACCEPTED IN THE ICPR2020 GENERAL ** ?? **? SESSION AND FITTING MAES TOPICS COULD BE SUBMITTED HERE !!! *** ??? ----> https://easychair.org/conferences/?conf=maesicpr2020 <---- _______________________________________________________________________ ?=== Aim & Scope === Environmental data are growing steadily in volume, complexity and diversity to Big Data mainly driven by advanced sensor technology. Machine learning can offer superior techniques for unravelling complexity, knowledge discovery and predictability of Big Data environmental science. The aim of the workshop is to provide a state-of-the-art survey of environmental research topics that can benefit from Machine Learning methods and techniques. To this purpose the workshop welcomes papers on successful environmental applications of machine learning and pattern recognition techniques to? diverse domains of Environmental Research, for instance, recognition of biodiversity in thermal, photo and acoustic images, natural hazards analysis and prediction, environmental remote sensing, estimation of environmental risks, prediction of the concentrations of pollutants in geographical areas, environmental threshold analysis and predictive modelling, estimation of Genetical Modified Organisms (GMO) effects on non-target species. The workshop will be the place to make an analysis of the advances of Machine Learning for the Environmental Science and should indicate the open problems in environmental research that still have not properly benefited from Machine Learning. Extended papers of this workshop will be published as a special issue in the journal of Environmental Modelling and Software, Elsevier. *** Due to the COVID pandemic, the workshop will be taken fully virtual. All accepted papers will be published. *** ?=== Invited Talk === "Harnessing big environmental data by machine learning", prof. Friedrich Recknagel, School of Biological Sciences, University of Adelaide, Australia (prof. Recknagel's bio: http://www.adelaide.edu.au/directory/friedrich.recknagel) (talk abstract: https://drive.google.com/file/d/12BFBiG4pwN-6TRKCy0OuGHOgue4YbOKJ/view?usp=sharing) ?=== Important Dates === -? 25 October? 2020 - workshop submission deadline (*EXTENDED*) -? 10 November 2020 - author notification -? 15 November 2020 - camera-ready submission -?? 1 December 2020 - finalized workshop program ?=== Organizers === ? Francesco Camastra, Universita' di Napoli Parthenope, Italy ?Friedrich Recknagel, University of Adelaide, Australia ??? Antonino Staiano, Universita' di Napoli Parthenope, Italy ?== Publicity chair == ????? Fabio Bellavia, Universita' di Palermo, Italy _______________________________________________________________________ ?Contacts: antonino.staiano at uniparthenope.it ?????????? francesco.camastra at uniparthenope.it ?Workshop: https://sites.google.com/view/maes-icpr2020/ ?ICPR2020: https://www.micc.unifi.it/icpr2020/ From pgarner at idiap.ch Tue Oct 20 11:13:50 2020 From: pgarner at idiap.ch (Phil Garner) Date: Tue, 20 Oct 2020 17:13:50 +0200 Subject: Connectionists: PhD position in ASR & NLP Message-ID: <8c54f35e-86b9-a879-0019-9c546350e08a@idiap.ch> Dear Colleagues, There is a fully funded PhD position open at Idiap Research Institute on "Speech recognition and natural language processing for digital interviews". At a high level, we are interested in how candidates for jobs respond in structured selection interviews; in particular how they are able to tell stories about past work situations. More concretely, we will investigate speech recognition architectures suitable for such interviews, and natural language processing solutions that are able to infer the higher level semantics required by our collaborators in the social sciences. A-priori, given that it is the higher level semantics that are of interest, we expect to make use of recent lexicon-free approaches to speech recognition. We also expect to draw from the rapidly advancing language modelling field with tools such as BERT and its successors. There will be ample opportunity for research in the component technologies, which are all currently pertinent in the general machine learning landscape. In particular, we expect to make advances in the technological interfaces between component technologies, and in the humanist interfaces between the machine learning practitioners and social scientists. For more information, and to apply, please follow this link: http://www.idiap.ch/education-and-jobs/job-10312 Idiap is located in Martigny in French speaking Switzerland, but functions in English and hosts many nationalities. PhD students are registered at EPFL. All positions offer quite generous salaries. Martigny has a distillery and a micro-brewery and is close to all manner of skiing, hiking and mountain life. There are other open positions on Idiap's main page https://www.idiap.ch/en/join-us/job-opportunities Sincerely, -- Phil Garner http://www.idiap.ch/~pgarner From pjthomas at case.edu Tue Oct 20 23:00:39 2020 From: pjthomas at case.edu (Peter Thomas) Date: Tue, 20 Oct 2020 23:00:39 -0400 Subject: Connectionists: Virtual Workshop on Motor Control October 26-29, 2020 Message-ID: Dear Colleagues Together with Hillel Chiel (CWRU) and Silvia Daun (University of Cologne) I invite you to participate in an online workshop on motor control on October 26-29, 2020. Topics will span theory and experiment, and systems ranging from vertebrate to invertebrate, from locomotion to cardiorespiratory control. Talks begin at 10:00 am US Eastern time. Please find attached the full schedule. The workshop will be run as a zoom webinar (access details follow). Talks will be recorded, technology permitting. Please contact motor-control-workshop-2020 at case.edu with any questions. Sincerely Peter Thomas Hi there, You are invited to a Zoom webinar. When: Oct 26, 2020 10:00 AM Eastern Time (US and Canada) Every day, 4 occurrence(s) Oct 26, 2020 10:00 AM Oct 27, 2020 10:00 AM Oct 28, 2020 10:00 AM Oct 29, 2020 10:00 AM Please download and import the following iCalendar (.ics) files to your calendar system. Daily: https://cwru.zoom.us/webinar/tJMrdOitrj0iHNAJwd0ZGUJKwk0Agl0O3bdd/ics?icsToken=98tyKuCvqDgrH9STuB-DRowEBIjCd-_ziCFHgo18tgjhUxp0VyndIekSE7VzQPeD Topic: 2020 Virtual Motor Control Workshop Please click the link below to join the webinar: https://cwru.zoom.us/j/97631506864?pwd=ZG1kZFcvc0hGeE11TGNvNDFnRlJldz09 Passcode: 817971 Or iPhone one-tap : US: +16465588656,,97631506864# or +13017158592,,97631506864# Or Telephone: Dial(for higher quality, dial a number based on your current location): US: +1 646 558 8656 or +1 301 715 8592 or +1 312 626 6799 or +1 669 900 6833 or +1 253 215 8782 or +1 346 248 7799 Webinar ID: 976 3150 6864 International numbers available: https://cwru.zoom.us/u/aegjtyRjc7 Or an H.323/SIP room system: H.323: 162.255.37.11 (US West) 162.255.36.11 (US East) 221.122.88.195 (China) 115.114.131.7 (India Mumbai) 115.114.115.7 (India Hyderabad) 213.19.144.110 (Amsterdam Netherlands) 213.244.140.110 (Germany) 103.122.166.55 (Australia) 209.9.211.110 (Hong Kong SAR) 149.137.40.110 (Singapore) 64.211.144.160 (Brazil) 69.174.57.160 (Canada) 207.226.132.110 (Japan) Meeting ID: 976 3150 6864 Passcode: 817971 SIP: 97631506864 at zoomcrc.com Passcode: 817971 -- Peter J. Thomas Professor Case Western Reserve University Department of Mathematics, Applied Mathematics and Statistics. Co-Editor-in-Chief, *Biological Cybernetics. * https://link.springer.com/journal/422 homepage: http://www.case.edu/math/thomas/ g-scholar: http://scholar.google.com/citations?user=5ctD7qIAAAAJ -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: 2020 Motor Control Workshop - schedule.pdf Type: application/pdf Size: 38934 bytes Desc: not available URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: Motor Control 2020 Titles and Abstracts.pdf Type: application/pdf Size: 101040 bytes Desc: not available URL: From interdonatos at gmail.com Wed Oct 21 04:15:26 2020 From: interdonatos at gmail.com (Roberto Interdonato) Date: Wed, 21 Oct 2020 10:15:26 +0200 Subject: Connectionists: CfP - Urban Complex Systems 2020 @ Conference on Complex Systems 2020 (CCS2020) Message-ID: CFP Urban Complex Systems 2020 @CCS2020 Urban Complex Systems December 09 -10, 2020 An Online Workshop Satellite of the Conference on Complex Systems 2020 Submission deadline: October 28, 2020 Acceptance notification: November 06, 2020 *Invited Speakers (TBU)* *Luca Maria Aiello, Nokia Bells Lab Cambridge, UK* *J?rg Menche, University of Vienna, Austria* *Alessandro Rizzo, Politecnico di Torino, Italy* Cities are massive systems whose tremendous complexity requires even greater efforts to be modeled, analyzed, understood and governed. The city is the expression of a multitude of strongly intertwined systems that vary from people sociality to transport systems, from the cultural fabric to urban planning. Each of these city facets already represents in itself a complex system but their interconnection represents what is certainly one of the systems created by human beings with highest complexity in the world. The aim of this event is to bring together researchers and practitioners from around the world interested in urban systems from the perspective of complexity science. Topics of interest include but are not limited to theoretical aspects, algorithms, methods, and fields of applications, such as: ? Urban Analytics ? Social networks ? Human behavior ? Information diffusion ? Epidemic spreading ? Mobility and transportation ? City services & infrastructures ? City monitoring ? Urban planning ? Communication systems ? Economic and financial systems ? Healthcare ? Emergency management ? Smart environment & ecosystems ? Digital city and smart growth ? Sustainability and energy efficiency ? Smart buildings and smart grids ? Manufacturing and logistics ? Intelligent infrastructure ? Blockchain for Smart City Applications *CONTRIBUTION:* Two types of contributions are welcome: ? *Extended Abstracts* about published or unpublished research (2to 3 pages including references). ? *Original research papers* discussing ongoing research projects (10 to 12 pages including references). They must follow the BioMed Central article template available at: https://appliednetsci.springeropen.com/submission-guidelines/preparing-your-manuscript/research-articles *PUBLICATION:* Accepted submission will be invited to submit an extended version of their contribution (either type) to a special issue of Applied Network Science edited by Springer *SUBMISSION WEBSITE* https://easychair.org/conferences/?conf=urbancomplexsystems2 *PC-CHAIRS* Hocine Cherifi *LIB University of Burgundy, France, **hocine.cherifi at gmail.com* Sabrina Gaito *Universit? degli Studi di Milano, Italy, **sabrina.gaito at unimi.it* Roberto Interdonato *CIRAD, UMR Tetis, Montpellier, France, **roberto.interdonato at cirad.fr* Hamamache Kheddouci *LIRIS Univ. of Lyon, France * *hamamache.kheddouci at univ-lyon1.fr* Matteo Zignani *Universit? degli Studi di Milano, Italy, **matteo.zignani at unimi.it* -------------- next part -------------- An HTML attachment was scrubbed... URL: From ASIM.ROY at asu.edu Wed Oct 21 03:48:24 2020 From: ASIM.ROY at asu.edu (Asim Roy) Date: Wed, 21 Oct 2020 07:48:24 +0000 Subject: Connectionists: INTERNATIONAL NEURAL NETWORK SOCIETY (INNS) - FREE Inaugural Virtual Workshop on Explainable AI on November 6, 2020, Friday, 9 am to 1 pm EST - REGISTRATION IS OPEN NOW Message-ID: Dear Colleagues, We are pleased to announce that INNS (the International Neural Network Society) is launching a Virtual Technical Event series that will feature workshops, seminars, tutorials, discussions and so on. These technical events will occur throughout the year for a worldwide audience. We welcome proposals on challenging and controversial research topics and ones that provide new insights on biological learning. Through this series of virtual technical events, we would like to serve the growing need for advanced education in a variety of fields that are linked together such as AI, machine learning, neural networks, cognitive science, robotics and so on. Further details on proposal submission are available at https://www.inns.org/virtual-technical-events. We also welcome proposals from the industry and industry sponsorship of these events. FREE Inaugural Virtual Workshop on Explainable AI on November 6, 2020, Friday, 9 am to 1 pm EST This inaugural workshop focuses on Explainable AI (XAI), a topic that is highly important for us to widely deploy our AI/ML systems. We invited five prominent scholars to present their thoughts in this virtual workshop. Further details are provided below including where to register for the event. WORKSHOP SPEAKERS 1. Stephen Grossberg, Wang Professor of Cognitive and Neural Systems, Boston University, http://sites.bu.edu/steveg/ 2. Juergen Schmidhuber, Scientific Director of IDSIA, http://people.idsia.ch/~juergen/ 3. Jeff Krichmar, Professor of Cognitive Sciences, University of California, Irvine, http://www.socsci.uci.edu/~jkrichma 4. Vladimir Cherkassky, Professor of ECE, Univ. of Minnesota, https://ece.umn.edu/directory/cherkassky-vladimir/ 5. Lee Giles, Professor of Information Sciences, Pennsylvania State University, https://clgiles.ist.psu.edu/ MODERATORS: Asim Roy, Professor, Arizona State University (https://lifeboat.com/ex/bios.asim.roy) Daniel Levine, Professor, University of Texas at Arlington (https://www.uta.edu/psychology/people/daniel-levine.php) FORMAT: Each speaker - 35 minute presentation + 10 mins Q&A REGISTRATION - https://www.eventbrite.hk/e/explainable-ai-xai-virtual-workshop-registration-122938932657 With regards, Irwin King INNS President, FIEEE, FHKIE, DMACM, BoG APNNS & INNS Chair, Dept. of Computer Science & Engineering o +(852) 3943-8398 The Chinese University of Hong Kong f +(852) 2603-5024 Shatin, N.T., Hong Kong http://www.cse.cuhk.edu.hk/irwin.king Asim Roy VP, Industry Relations, INNS Chair, Committee for Virtual Technical Events, INNS Professor, Arizona State University https://lifeboat.com/ex/bios.asim.roy -------------- next part -------------- An HTML attachment was scrubbed... URL: From Auke.Ijspeert at epfl.ch Wed Oct 21 10:05:53 2020 From: Auke.Ijspeert at epfl.ch (Auke Ijspeert) Date: Wed, 21 Oct 2020 16:05:53 +0200 Subject: Connectionists: PhD and postdoc position in quadruped robotics and machine learning at EPFL, Lausanne Switzerland Message-ID: The Biorobotics laboratory (Biorob, https://www.epfl.ch/labs/biorob/ ) at EPFL (Lausanne, Switzerland) has one open *PhD student* and one *postdoc position* in *quadruped robotics and machine learning*.? The project is at the intersection between robotics, machine learning, and computational neuroscience. Its goal is is to develop a computational architecture that (i) merges spinal-cord-like dynamics with higher-level planning and learning, (ii) allows testing hypotheses about animal motor control at a conceptual level, and (iii) can serve as basis for controlling, planning, and learning rich motor skills in robots. The architecture will be evaluated with a scenario that involves control and learning in a quadruped robot crossing a (simple) parkour. The positions are fully funded for 4 years through a grant from the Swiss National Science Foundation. EPFL is one of the leading Institutes of Technology in Europe and offers extremely competitive salaries and research infrastructure. *Instructions to apply* can be found here: https://www.epfl.ch/labs/biorob/openings/ *The ideal starting date is early 2021* (with some flexibility). Applications will be considered starting *from November 15 2020*, and then continuously until the positions are filled. Best regards, Auke Ijspeert -- ----------------------------------------------------------------- Prof Auke Jan Ijspeert Biorobotics Laboratory EPFL-STI-IBI-BIOROB, ME D1 1226, Station 9 EPFL, Ecole Polytechnique F?d?rale de Lausanne CH 1015 Lausanne, Switzerland Office: ME D1 1226 Tel: +41 21 693 2658 Fax: +41 21 693 3705 www:http://biorob.epfl.ch Email:Auke.Ijspeert at epfl.ch ----------------------------------------------------------------- -------------- next part -------------- An HTML attachment was scrubbed... URL: From chhavi at nyu.edu Thu Oct 22 01:07:37 2020 From: chhavi at nyu.edu (Chhavi Yadav) Date: Wed, 21 Oct 2020 22:07:37 -0700 Subject: Connectionists: Announcing Trustworthy ML Initiative and Virtual Seminar Series (starts Oct 29) Message-ID: (Apologies for cross posting) Hi all, We wanted to share an initiative we launched recently: Trustworthy ML Initiative (TrustML). A major focus of the initiative is a bi-weekly virtual seminar series where speakers discuss their work in various subfields of Trustworthy ML, such as explainability, fairness, differential privacy, causality, robustness, etc. The first seminar starts next Thursday Oct 29, 9am PT / 5pm London / 7pm Addis Ababa. *We would like to invite you to attend the seminar and participate in the post-seminar discussion!* Our confirmed speakers include Percy Liang, Ayanna Howard, Irene Chen, Jenn Wortman Vaughan, Cynthia Rudin, Pin-Yu Chen, Zachary Lipton, Steven Wu, Shibani Santurkar, Celia Cintas, Katherine Heller, Gautam Kamath, Suresh Venkatasubramanian, Sherri Rose, Alexander D'Amour, and more to come! As part of our seminar series, we are also featuring students in Rising Star Spotlight Talks. Please contact us at trustworthyml at gmail.com if you are a student and want to present your work. To enable easy access of fundamental resources in the field, we have also collected links to courses, textbooks, videos, etc. on our website. We also manage an active Twitter account @trustworthy_ml that disseminates the latest work in trustworthy ML. We welcome you to engage with our resources, attend our seminars, and send us your work to be disseminated. All feedback is welcome! On behalf of the Trustworthy ML Initiative organizers and advisors, Hima Lakkaraju (Harvard) Sara Hooker (Google Brain) Sarah Tan (Facebook) Subho Majumdar (AT&T Labs Research) Chhavi Yadav (UCSD) Jaydeep Borkar (Pune University) Kamalika Chaudhuri (UCSD) Tom Dietterich (Oregon State University) Kush Varshney (IBM Research) ************************ *More about the Trustworthy ML initiative: *As machine learning (ML) systems are increasingly being deployed in real-world applications, it is critical to ensure that these systems are behaving responsibly and are trustworthy. To this end, there has been growing interest from researchers and practitioners to develop and deploy ML models and algorithms that are not only accurate, but also explainable, fair, privacy-preserving, causal, and robust. This broad area of research is commonly referred to as trustworthy ML. While it is incredibly exciting that researchers from diverse domains ranging from machine learning to health policy and law are working on trustworthy ML, this has also resulted in the emergence of critical challenges such as information overload and lack of visibility for work of early career researchers. Furthermore, the barriers to entry into this field are growing day-by-day -- researchers entering the field are faced with an overwhelming amount of prior work without a clear roadmap of where to start and how to navigate the field. To address these challenges, we are launching the Trustworthy ML Initiative (TrustML) with the following goals: - Enable easy access of fundamental resources to newcomers in the field. - Provide a platform for early career researchers to showcase and disseminate their work. - Encourage discussion and debate on the latest work on trustworthy ML. - Develop a community of researchers and practitioners working on topics related to trustworthy ML. Please check our website www.trustworthyml.org for our ongoing efforts and programs! -------------- next part -------------- An HTML attachment was scrubbed... URL: From Pavis at iit.it Thu Oct 22 08:03:43 2020 From: Pavis at iit.it (Pavis) Date: Thu, 22 Oct 2020 12:03:43 +0000 Subject: Connectionists: 2x Postdoc positions on deep learning for 2D/2.5D/3D scene understanding- IIT GENOVA - ITALY Message-ID: <3e25e3b6c3af45b6a0637adb47406e32@iit.it> The Pattern Analysis and Computer Vision (PAVIS) Research Line at Fondazione Istituto Italiano di Tecnologia - IIT invites qualified candidates to submit their applications for a Postdoc position in Genoa, Italy under the supervision of Dr Alessio Del Bue. THE GROUP: PAVIS Research Line is actively developing an Artificial Intelligence (AI) infrastructure to understand our physical space and the human behaviours within it. The focus of the group is on creating intelligent systems that jointly accomplish two main goals: - Spatial AI: Perceive and understand autonomously the real physical world, both static and dynamic, with its corresponding spatial semantic (where are things, what is their function, which is the dynamic of the scene). - Social AI: Perceive and understand humans and their behaviours as observed by cameras in relation to the physical spaces they are interacting with. RESEARCH TOPICS: Topics include: - Object 3D localization small to large scale - 2D/3D Scene Graph modelling using Graph Neural Networks - Integrating deep learning models with multi-view geometry - Semantic Simultaneous Localization and Mapping (S-SLAM) - Semantic structure from motion (S-SfM) - Language and Vision including Visual Question and Answering - Retrieval and Knowledge-based Computer Vision - Zero/Few Shot Learning Details: - Competitive salary commensurate to qualifications and experience - One of the roles is financed in the context of the H2020 European Project MEMEX (MEMories and EXperiences for inclusive digital storytelling ? Grant Agreement 870743 -https://www.memexproject.eu) YOUR EXPERIENCE: Required: - Relevant scientific track record on major computer vision conferences/journals (CVPR, ICCV, ECCV, TPAMI, IJCV, etc.) - Experience on DNN models and, in particular, related to GNN - PhD degree in Computer Vision, Machine Learning, Robotics or related fields - Good communication skills and ability to cooperate - Proficient in English language (written and oral) Desired: - Experience in multi-view geometry - Experience in High-Performance Computing - Knowledge of AR/VR related software (e.g., ARKit, ARCore, Unity) - Knowledge of web services TO APPLY Required Documents: - Detailed curriculum vitae - Publication list - Cover Letter explaining your interest in PAVIS (& the MEMEX Project) and its research interests - Brief statement of research - Names and contact details of 2 referees Please submit your application using the online form for one or both of the positions: - PostDoc 1 https://iit.taleo.net/careersection/ex/jobdetail.ftl?lang=en&job=2000002W - PostDoc 2 (on the MEMEX Project): https://iit.taleo.net/careersection/ex/jobdetail.ftl?lang=en&job=2000002K The call will remain open until the position is filled but a first deadline for evaluation of candidates will be November 5th, 2020. The position on the MEMEX project will be approved pending signature of the grant agreement by the European Commission. THE INSTITUTE Fondazione Istituto Italiano di Tecnologia - IIT - was founded with the objective of promoting Italy?s technological development and further education in science and technology. In this sense, IIT is committed to achieving its scientific program, which sees a major inspirational principle in the integration between basic scientific research and the development of technical applications. Research activities at IIT cover areas of high innovative content, representing the most advanced frontiers of modern technology with wide application possibilities in various fields from medicine to industry, from computer science to robotics, life sciences and nanobiotechnology. Istituto Italiano di Tecnologia is an Equal Opportunity Employer that actively seeks diversity in the workforce. Please note that the data that you provide will be used exclusively for the purpose of professional profiles? evaluation and selection, and in order to meet the requirements of Istituto Italiano di Tecnologia. Your data will be processed by Istituto Italiano di Tecnologia, based in Genoa, Via Morego 30, acting as Data Controller, in compliance with the rules on protection of personal data, including those related to data security. Please also note that, pursuant to articles 15 et. seq. of European Regulation no. 679/2016 (General Data Protection Regulation), you may exercise your rights at any time by contacting the Data Protection Officer (phone +39 010 71781 - email: dpo[at]iit.it). -------------- next part -------------- An HTML attachment was scrubbed... URL: From martaruizcostajussa at gmail.com Thu Oct 22 06:20:32 2020 From: martaruizcostajussa at gmail.com (Marta Ruiz) Date: Thu, 22 Oct 2020 12:20:32 +0200 Subject: Connectionists: =?utf-8?q?PhD_position_in_Natural_Language_Proces?= =?utf-8?q?sing_at_Universitat_Polit=C3=A8cnica_de_Catalunya?= Message-ID: Job openings: 1 PhD position in Machine Learning and Natural Language Processing at Universitat Polit?cnica de Catalunya, Barcelona Project: LUNAR ("Lifelong UNiversal lAnguage Representation"), ERC Starting Grant (2020-2025) Application deadline: November 15, 2020 Job requirements: Bachelor?s degree and a master?s degree in the field of computer science/engineering or mathematics. Python programming. Experience in Deep Learning. Job description: There is one open position for a PhD researcher in the scope of the ERC project LUNAR ("Lifelong UNiversal lAnguage Representation"). This project addresses the low-resources problem and the expensive approach to multilingual machine translation since systems for all translation pairs are required. LUNAR proposes to jointly learn a multilingual and multimodal model that builds upon a lifelong universal language representation. This model will compensate for the lack of supervised data and significantly increase the system capacity of generalization from training data given the unconventional variety of employed resources. This model will reduce the number of required translation systems from quadratic to linear as well as allowing for an incremental adaptation of new languages and data. The role of this PhD is to focus on the common multilingual text representation and the integration of partial resources. This offer is a 3-year PhD position. If interested in this position, please send an email with your CV to marta.ruiz AT upc.edu and the subject title ?[LUNAR] PhD Position?. Feel free to contact me for any further information. Working environment: The host institution (Universitat Polit?cnica de Catalunya) is a public institution of research and higher education in the fields of engineering, architecture, sciences and technology, and one of the leading technical universities in Europe. Every year, more than 6,000 bachelor?s and master?s students and more than 500 doctoral students graduate, more than 3,000 faculty members, and a total of 12 ERC grants. The principal investigator is part of the ELLIS network . Collaborations with other ELLIS members are encouraged. Salary: 1,200-1,400 (free of tax) euros More info about the research group at MT-UPC -- Marta Ruiz Costa-juss? http://www.costa-jussa.com -------------- next part -------------- An HTML attachment was scrubbed... URL: From martaruizcostajussa at gmail.com Thu Oct 22 06:23:33 2020 From: martaruizcostajussa at gmail.com (Marta Ruiz) Date: Thu, 22 Oct 2020 12:23:33 +0200 Subject: Connectionists: =?utf-8?q?PostDoc_Position_in_Speech_and_Natural_?= =?utf-8?q?Language_Processing_at_the_Universitat_Polit=C3=A8cnica_?= =?utf-8?q?de_Catalunya?= Message-ID: Job openings: 1 PostDocs position in Speech and Natural Language Processing at Universitat Polit?cnica de Catalunya, Barcelona Project: LUNAR ("Lifelong UNiversal lAnguage Representation"), ERC Starting Grant (2020-2025) Application deadline: November 15, 2020 Job requirements: PhD in the field of computer science/engineering or mathematics. Python programming. Experience in Deep Learning and Speech and Natural Language Processing. Job description: There is one open position for a PhD researcher in the scope of the ERC project LUNAR ("Lifelong UNiversal lAnguage Representation"). This project addresses the low-resources problem and the expensive approach to multilingual machine translation since systems for all translation pairs are required. LUNAR proposes to jointly learn a multilingual and multimodal model that builds upon a lifelong universal language representation. This model will compensate for the lack of supervised data and significantly increase the system capacity of generalization from training data given the unconventional variety of employed resources. This model will reduce the number of required translation systems from quadratic to linear as well as allowing for an incremental adaptation of new languages and data. The role of this Postdoc is to research on the common multilingual/multimodal representation, multitasking and unsupervised approaches. This offer is a 1-year PostDoc position extendable on a year basis to 4-years (in total). If interested in this position, please send an email with your CV to marta.ruiz AT upc.edu and the subject title ?[LUNAR] PostDoc Position?. Feel free to contact me for any further information. Working environment: The host institution (Universitat Polit?cnica de Catalunya) is a public institution of research and higher education in the fields of engineering, architecture, sciences and technology, and one of the leading technical universities in Europe. Every year, more than 6,000 bachelor?s and master?s students and more than 500 doctoral students graduate, more than 3000 faculty members, and 12 ERC grants. The principal investigator is part of the ELLIS network . Collaborations with other ELLIS members are encouraged. Salary: 2,300-2,700 euros (free of tax) More info about the research group at MT-UPC -- Marta Ruiz Costa-juss? Researcher at Universitat Polit?cnica de Catalunya marta.ruiz at upc.edu http://www.costa-jussa.com -------------- next part -------------- An HTML attachment was scrubbed... URL: From sylvia.schroeder at ucl.ac.uk Thu Oct 22 15:58:28 2020 From: sylvia.schroeder at ucl.ac.uk (=?UTF-8?Q?Sylvia_Schr=c3=b6der?=) Date: Thu, 22 Oct 2020 20:58:28 +0100 Subject: Connectionists: =?utf-8?q?Postdoctoral_position_on_the_integratio?= =?utf-8?q?n_of_vision_and_behaviour_=28Schr=C3=B6der_Lab=2C_University_of?= =?utf-8?q?_Sussex=2C_UK=29?= Message-ID: The Schr?der Lab (Vision and Behaviour) at the University of Sussex, UK, offers a position for a *Postdoctoral researcher*** to study information processing in the early visual system of mice using two-photon imaging, electrophysiology (Neuropixels probes), and opto- and chemogenetic manipulations. The lab?s goal is to determine how behavioural and internal states like arousal are integrated with visual responses in the retina and superior colliculus. We want to discover the underlying mechanisms and the purpose of this integration in terms of visual processing and the animal?s behavioural demands. This paper describes our previous findings. *Your profile* ?Phd degree in neuroscience or in physics, computer science or engineering with a keen interest in neuroscience ?You will take ownership of the project and drive it forward ?Experience in experimental biology and quantitative data analysis including programming in Python, Matlab or a similar language ?Experience with two-photon imaging and/or extracellular electrophysiology desirable *Our offer to you* The Schr?der lab opens its doors in January 2021. The candidate will have the opportunity: ?to make use of the lab?s own two-photon microscopy and Neuropixels recording setups ?to benefit from the PI?s active support in research and her mentoring in career development ?to learn essential skills in organising and setting up a lab ?to shape the research culture of the lab based on the values of scientific excellence, team work, and diversity** *Appointment* The position is offered for 2 years initially and is funded through a Sir Henry Dale Fellowship (for 5 years) sponsored by the Wellcome Trust. Starting salary is between ?33,797to ?38,017 per annum depending on experience.** *Environment* The lab is integrated within Sussex Neuroscience , which gives the researcher the opportunity to collaborate and benefit from the expertise of other labs in fields like the visual and other sensory systems, mouse behaviour, techniques of two-photon imaging and electrophysiology, and computational neuroscience. The campus of University of Sussex is located just outside the vibrant city of Brighton at the coast of South East England, one hour away from London. It is surrounded by the South Downs National Park. *Starting date* January 2021 or later *How to apply* Please, see details in the job advertisement . Applications should be accompanied by a CV (2-3 pages), a statement of your research interests and relevant skills (1 page), and contact information of 2-3 referees. Applications must be received by 1st December, 2020. Informal enquiries are highly encouraged and should be made to Sylvia Schr?der (sylvia.schroeder at ucl.ac.uk ). -------------- next part -------------- An HTML attachment was scrubbed... URL: From hcomp.publicity at gmail.com Thu Oct 22 13:11:55 2020 From: hcomp.publicity at gmail.com (HCOMP Publicity) Date: Thu, 22 Oct 2020 19:11:55 +0200 Subject: Connectionists: HCOMP2020: Call for Participation Message-ID: Apologies for cross-posting * We invite you to attend the 8th AAAI Conference on Human Computation and Crowdsourcing (HCOMP 2020), which will be held on October 25-29 virtually at The Netherlands Institute for Sound and Vision in Hilversum, The Netherlands. https://www.humancomputation.com HCOMP is the home of the human computation and crowdsourcing community. It?s the premier venue for presenting latest findings from research and practice into frameworks, methods and systems that bring together people and machine intelligence to achieve better results. While artificial intelligence (AI) and human-computer interaction (HCI) represent traditional mainstays of the conference, HCOMP believes strongly in fostering and promoting broad, interdisciplinary research. Our field is particularly unique in the diversity of disciplines it draws upon and contributes to, including human-centred qualitative studies and HCI design, social computing, artificial intelligence, economics, computational social science, digital humanities, policy, and ethics. We promote the exchange of advances in human computation and crowdsourcing not only among researchers, but also engineers and practitioners, to encourage dialogue across disciplines and communities of practice. This year?s conference theme is around the quality or qualities of human-annotated datasets. The programme features: Exciting keynotes: https://www.humancomputation.com/keynotes.html Julia Noordegraaf , University of Amsterdam Pietro Perona , Amazon Anna Ridler , Artist Chris Welty , Google Mounia Lalmas , Spotify Doctoral Consortium track providing mentoring to PhD students HCOMP2020 Social events: BOOM CHICAGO will make sure we have sufficient fun during the conference days. Check out our HCOMP2020 trailer . Sponsored by Sound and Vision HAND-DRAWN SKETCHES - Elco van Staveren of Denkschets.nl will visualize with hand-drawn sketches the topics and events at the conference Sponsored by Sound and Vision New at HCOMP: Data Challenge will be presented during the HCOMP CrowdCamp - specifically addressing the topics of the conference in terms of data quality https://www.humancomputation.com/submit.html#ccamp Organized by IBM and Google Wednesday Oct 28, 2020, 3:00 pm - 5:30 pm CET Blue Sky track - in cooperation with the Computing Community Consortium (CCC) will present visionary ideas, long term challenges, and opportunities in HCOMP research https://www.humancomputation.com/papers.html#bsi Organized by Ujwal Gadiraju (TU Delft) Thursday Oct 29, 2020, 3:00 pm - 3:50 pm CET 2 Exciting Workshops focussing on Data and AI evaluation practices: Data Excellence Workshop (DEW2020) Monday, Oct 26, 2020, 2:00 pm - 6:20 pm CET Rigorous Evaluation of AI Systems (REAIS2020) Sunday, Oct 25, 2020, 2:00 pm - 6:20 pm CET If you?re interested in attending, you can find more information about how to register here for the whole conference to experience all this, or workshops only. All the video recordings from the conference will be available after the conference with your registration. We?re looking forward to meeting you at HCOMP starting from Sunday, October 25. Elena Simperl, King?s College London & Lora Aroyo, Google, HCOMP2020 general chairs -------------- next part -------------- An HTML attachment was scrubbed... URL: From zoltan.szabo.list at zoho.com Thu Oct 22 12:32:41 2020 From: zoltan.szabo.list at zoho.com (Zoltan Szabo) Date: Thu, 22 Oct 2020 18:32:41 +0200 Subject: Connectionists: StressTest-2020 workshop: registration is open Message-ID: Dear All, This is an announcement about the StressTest-2020 Workshop on financial stress-testing, uncertainty quantification, risk and dependence modelling. The event will take place online on the 30th Nov - 1st Dec, 2020 (2:00-5:30pm, Paris time). Speakers: -Agostino Capponi: Columbia University -Anne Sabourin: T?l?com Paris -Claude Martini: Zeliade Systems -Dorinel Bastide: BNP STFS -Elisa Ndiaye: BNP STFS -Silvana Pesenti: University of Toronto -Stefano Battiston: University of Z?rich -St?phane Cr?pey: University of ?vry The registration is free but mandatory. You are welcome to join: https://stresstest2020.sciencesconf.org/ Best, Zoltan, on behalf of the organizers -- Zoltan Szabo Center of Applied Mathematics (CMAP) Ecole Polytechnique http://www.cmap.polytechnique.fr/~zoltan.szabo? From dorien.herremans at gmail.com Fri Oct 23 02:34:31 2020 From: dorien.herremans at gmail.com (Dorien Herremans) Date: Fri, 23 Oct 2020 14:34:31 +0800 Subject: Connectionists: Job opening - Finance RA Message-ID: We are looking for a motivated wizard in neural networks to research and develop sequential time series and NLP models for finance in PyTorch to join our team at SUTD. Some key skills required: - Passion for PyTorch, including the latest NN like Bert, self-attention, LSTMs and efficient data loading. - Knowledge of the latest NLP models - Experience parsing datasets from the web - Interest in financial predictions and basic knowledge of market data and financial indicators - Scientific writing skills in LaTeX and interest to disseminate the research - Ability to work independently. You will be working on an initial 6-month contract, subject to extension pending funding. For more info, contact dorien_herremans at sutd.edu.sg with subject [RA finance]. #bert #nlp #pytorch #job -- Dorien Herremans, PhD Assistant Professor, ISTD & DAI Director, SUTD Game Lab http://dorienherremans.com Singapore University of Technology and Design Information Technology and Design Pillar Office 1.502-18 -------------- next part -------------- An HTML attachment was scrubbed... URL: From tongzhang at ust.hk Fri Oct 23 08:10:59 2020 From: tongzhang at ust.hk (Tong ZHANG) Date: Fri, 23 Oct 2020 12:10:59 +0000 Subject: Connectionists: Machine Learning Postdoc and Research Assistant Positions Message-ID: <8AEFB309-D568-4355-81E3-966408D2024B@ust.hk> Dear Colleagues, There are post-doc and research assistant positions available at the Hong Kong University of Science and Technology in machine learning for financial data analysis under professor Tong Zhang. The group works on various topics ranging from machine learning theory, to optimization algorithms, to various applications. The postdoc employment period can be up to three years. The applicants should have strong programming skills and experience in machine learning. Interested candidates can send cv to professor Tong Zhang at tongzhang at ust.hk. ---- Tong Zhang Chair professor The Hong Kong University of Science and Technology -------------- next part -------------- An HTML attachment was scrubbed... URL: From stefanm at alleninstitute.org Fri Oct 23 12:23:17 2020 From: stefanm at alleninstitute.org (Stefan Mihalas) Date: Fri, 23 Oct 2020 16:23:17 +0000 Subject: Connectionists: =?utf-8?q?Scientist_I_position_at_Allen_Institute?= =?utf-8?q?_=E2=80=93_Modeling_Structure-Function_Relation_in_a_Reconstruc?= =?utf-8?q?ted_Cortical_Tissue?= In-Reply-To: References: Message-ID: Scientist I ? Modeling Structure-Function Relation in a Reconstructed Cortical Tissue Our mission at the Allen Institute is to advance our understanding of how the brain works in health and disease. Using a team science approach, we strive to discover how the brain implements fundamental computations through the integration of technological innovation, cutting-edge experiments, modeling, and theory. Understanding how the structure of biological neuronal networks leads to its observed activity, and how it relates to the implemented computations is one of the primary challenges in computational neuroscience. We have large datasets of in-vitro measured cell type properties (https://celltypes.brain-map.org/), statistical knowledge of their connections (https://portal.brain-map.org/explore/connectivity/synaptic-physiology) and large-scale recordings of their in-vivo activity (https://observatory.brain-map.org/visualcoding). These are complemented by a fantastic dataset of coupled structure-activity measurement at cell type level in one tissue (https://microns-explorer.org). We are seeking a scientist to join the Modeling and Theory team of Stefan Mihalas help construct data driven models of the activity and computations in the mouse cortex. Our team focuses at extracting principles from large data, integrating them in simplified models and using the models to test theories of computation. Even with all this data available, directly trying to simulate activity from structure is an under constrained problem. The scientist will work to compare existing algorithms to efficiently explore the space of models linking structure to activity and potentially develop new algorithms, if needed. The scientist will explore how additional constrains, including constraints imposed by computations, can be used to further narrow down the parameter space. To be able to explore the space of models efficiently, we intend to use on spiking neuron models, with a focus on generalized leaky integrate and fire models. The scientist will work as part of a team to use these methods to construct a set of models visually driven in vivo neuronal activity, and subsequently explore the computational properties of these models. Essential Functions * Implement and compare algorithms for automatic parameter optimization in spiking neural network models * Help design and construct data driven models for visually driven in vivo neuronal activity * Help explore the computational properties of the models * Contribute scientific ideas based on the modeling results * Develop and maintain computational and associated software tools * Publish/present findings in peer-reviewed journals and at scientific conferences * Maintain clear and accurate communication with supervisor and other team members Required Education and Experience * PhD in computational neuroscience, applied mathematics, computer science or a related field * 0-2 years of post-doctoral experience. * Strong computational/data analysis skills and good programming ability in Python * Strong written and verbal communication skills Preferred Education and Experience * Strong knowledge of systems neuroscience * Experience using PyTorch or TensorFlow * Experience simulating spiking neuronal networks using NEST * Ability to work as part of a collaborative team * Track record of scientific excellence and independent thinking Physical Demands * Fine motor movements in fingers/hands to operate computers and other office equipment; lab equipment Position Type/Expected Hours of Work * This role is currently able to work remotely due to COVID-19 and our focus on employee safety; this may change, and you may be required to work onsite at our South Lake Union office as safety restrictions are lifted in relation to COVID-19. It is the policy of the Allen Institute to provide equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, the Allen Institute will provide reasonable accommodations for qualified individuals with disabilities. Apply at: https://alleninstitute.hrmdirect.com/employment/job-opening.php?req=1416302&cust_sort1=29268%2Femployment%2Fjob-openings.php%3Fsearch%3Dtrue&nohd&csrc=37190 -------------- next part -------------- An HTML attachment was scrubbed... URL: From walter.senn at unibe.ch Fri Oct 23 10:14:46 2020 From: walter.senn at unibe.ch (Walter Senn) Date: Fri, 23 Oct 2020 16:14:46 +0200 Subject: Connectionists: Postdoc position on Biological Deep Learning Message-ID: Dear all A second postdoc position devoted to learning in deep cortical networks is available in our Computational Neuroscience labs at the University of Bern, Switzerland. This position is focussed on formulating error-based learning in deep cortical networks in terms of a principle of least action. We will extend this theory to natural gradient learning and to learning with spiking neurons. The research of our labs is more broadly devoted to biologically realistic models of spatio-temporal processing in cortical networks and their relation to reinforcement learning, Bayesian computing, and neuromorphic implementations. The position is part of the European Human Brain Project and is available by January 1st, 2021, for 2 years (extendable). We offer a stimulating environment with three research groups in theoretical and computational neuroscience, along with experimental neuroscience at the same Department of Physiology (physio.unibe.ch/gruppen.aspx ), as well as close collaborations with other labs in neuroscience, artificial intelligence and neuromorphic engineering. Ideal candidates should have a strong background in computational neuroscience, machine learning, applied mathematics and/or physics. Please send your CV, publication list, letter of motivation and contact information for at least two references to Walter Senn (walter.senn at unibe.ch ) and Mihai Petrovici (mihai.petrovici at unibe.ch ), with cc to Virginie Sabado (virginie.sabado at unibe.ch ). The first evaluation round will begin on November 8, 2020. The positions will remain open until filled. With best regards, Mihai Petrovici and Walter -------------- next part -------------- An HTML attachment was scrubbed... URL: From stefanm at alleninstitute.org Fri Oct 23 12:21:10 2020 From: stefanm at alleninstitute.org (Stefan Mihalas) Date: Fri, 23 Oct 2020 16:21:10 +0000 Subject: Connectionists: =?utf-8?q?Scientist_position_at_Allen_Institute_?= =?utf-8?q?=E2=80=93_Biological_constraints_of_computation?= In-Reply-To: References: Message-ID: <246ED075-6B3F-4E4F-BF89-BA118E85CF8C@alleninstitute.org> Scientist ? Biological constraints of computation Our mission at the Allen Institute is to advance our understanding of how the brain works in health and disease. Using a team science approach, we strive to discover how the brain implements fundamental computations through the integration of technological innovation, cutting-edge experiments, modeling, and theory. The defining aspect of the brain is its capacity to produce behavior. However, how behavior arises from the computations implemented by different systems in the brain, what is the set of computations implemented by different systems, and how this set of computations is limited by anatomical constraints remains poorly understood. We want to use anatomical data (http://connectivity.brain-map.org/) to constrain the space of architectures for the visual system, train models for different etologically relevant tasks, and compare model?s responses with those physiological observed (https://observatory.brain-map.org/visualcoding). One of the salient characteristics of the responses in the mouse visual system is the large variability of responses to the same images, and the combination of visual and motor responses. We seek to explore the space of tasks which produce similar representations to those observed in the mouse brain, with a focus on development of mixed visual/motor representations. The final results of the models trained on etologically relevant tasks can be used as initial states for models learning. We are seeking a scientist to join the Modeling and Theory team of Stefan Mihalas to help construct biologically constrained task driven models of the mouse cortex. The scientist will help transform biological knowledge of structure into architectural constraints, train models with such over a range of tasks, and compare the results to in vivo physiology measurements. The scientist is expected to have strong contributions at the level of ideas, and help shape future projects. Our team focuses at extracting principles from large data, integrating them in simplified models and using the models to test theories of computation. Essential Functions * Construct architectural constraints for the network from large scale connectivity data * Train models for visual processing with architectural constraints to perform different visual/motor tasks, and compare the results with the physiological recordings * In collaboration with experimentalists contribute to the analysis of the anatomical and physiological data * Contribute scientific ideas based on the modeling results, and help shape future projects * Develop and maintain computational and associated software tools * Maintain clear and accurate communication with supervisor and team members * Publish/present findings in peer-reviewed journals/scientific conferences Required Experience and Education * PhD degree in computational neuroscience, physics, mathematics, applied mathematics or related field. * Scientist I: 0-2 years of post-doctoral experience * Strong background in scientific computing and data analysis * Proven ability to code using Python and experience using PyTorch or TensorFLow * Strong written and verbal communication skills. Preferred Education and Experience * Experience in computational neuroscience * Ability to meet aggressive timelines and deliverables in a collaborative environment. Physical Demands * Fine motor movements in fingers/hands to operate computers and other office equipment; lab equipment Position Type/Expected Hours of Work * This role is currently able to work remotely due to COVID-19 and our focus on employee safety; this may change, and you may be required to work onsite at our South Lake Union office as safety restrictions are lifted in relation to COVID-19. It is the policy of the Allen Institute to provide equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, the Allen Institute will provide reasonable accommodations for qualified individuals with disabilities. Apply at: https://alleninstitute.hrmdirect.com/employment/job-opening.php?req=1279097&cust_sort1=29268%2Femployment%2Fjob-openings.php%3Fsearch%3Dtrue&nohd&csrc=37190 -------------- next part -------------- An HTML attachment was scrubbed... URL: From rava at ens.fr Sun Oct 25 16:11:41 2020 From: rava at ens.fr (Rava A. da Silveira) Date: Sun, 25 Oct 2020 21:11:41 +0100 Subject: Connectionists: POSTDOC POSITIONS IN COMPUTATIONAL NEUROSCIENCE IN PARIS AND BASEL Message-ID: *Several postdoctoral openings in the lab of Rava Azeredo da Silveira **(Paris & Basel)* The lab of Rava Azeredo da Silveira invites applications for *Postdoctoral Researcher* positions at ENS, Paris, and IOB, an associated institute of the University of Basel. Research questions will be chosen from a broad range of topics in theoretical/computational neuroscience and cognitive science (see the description of the lab?s activity, below). One of the postdoc positions to be filled in Basel will be part of a collaborative framework with Michael Woodford (Columbia University) and will involve projects relating the study of decision making to models of perception and memory. Candidates with backgrounds in mathematics, statistics, artificial intelligence, physics, computer science, engineering, biology, and psychology are welcome. Experience with data analysis and proficiency with numerical methods, in addition to familiarity with neuroscience topics and mathematical and statistical methods, are desirable. Equally desirable are a spirit of intellectual adventure, eagerness, and drive. The positions will come with highly competitive work conditions and salaries. *Application deadline:* Applications will be reviewed starting on 1 November 2020. *How to apply:* Please send the following information *in one single PDF, to * *silveira at iob.ch* *:* 1. letter of motivation; 2. statement of research interests, limited to two pages; 3. curriculum vit? including a list of publications; 4. any relevant publications that you wish to showcase. In addition, please arrange for three letters of recommendations to be sent to the same email address. In all email correspondence, please include the mention ?APPLICATION-POSTDOC? in the subject header, otherwise the application will *not* be considered. *** *ENS,* together with a number of neighboring institutions (College de France, Institut Curie, ESPCI, Sorbonne Universit?, and Institut Pasteur), offers a rich scientific and intellectual environment, with a strong representation in computational neuroscience and related fields. *IOB* is a research institute combining basic and clinical research. Its mission is to drive innovations in understanding vision and its diseases and develop new therapies for vision loss. IOB is an equal-opportunity employer with family-friendly work policies. *The Silveira** Lab* focuses on a range of topics, which, however, are tied together through a central question: How does the brain represent and manipulate information? Among the more concrete approaches to this question, the lab analyses and models neural activity in circuits that can be identified, recorded from, and perturbed experimentally, such as visual neural circuits in the retina and the cortex. Establishing links between physiological specificity and the structure of neural activity yields an understanding of circuits as building blocks of cerebral information processing. On a more abstract level, the lab investigates the representation of information in populations of neurons, from a statistical and algorithmic?rather than mechanistic?point of view, through theories of coding and data analyses. These studies aim at understanding the statistical nature of high-dimensional neural activity in different conditions, and how this serves to encode and process information from the sensory world. In the context of cognitive studies, the lab investigates mental processes such as inference, learning, and decision-making, through both theoretical developments and behavioral experiments. A particular focus is the study of neural constraints and limitations and, further, their impact on mental processes. Neural limitations impinge on the structure and variability of mental representations, which in turn inform the cognitive algorithms that produce behavior. The lab explores the nature of neural limitations, mental representations, and cognitive algorithms, and their interrelations. -------------- next part -------------- An HTML attachment was scrubbed... URL: From d.goodman at imperial.ac.uk Sun Oct 25 09:06:18 2020 From: d.goodman at imperial.ac.uk (Goodman, Daniel F M) Date: Sun, 25 Oct 2020 13:06:18 +0000 Subject: Connectionists: Neuromatch conference Oct 26-30 Message-ID: This is just a reminder that the Neuromatch conference starts tomorrow (at the time of writing) Oct 26-30. We have around 900 talks on all aspects of neuroscience, debates, panels, as well as special series in partnership with the BRAIN initiative, Black in Neuro, and Queer in Neuro. Check our our website here: https://www.neuromatch.io/ Registration is $25, but can be waived with the press of a button, no questions asked, if you're not able to pay. You can see the full agenda with recommendation engine once you've registered, or you can use our old fashioned schedule here before registering (but no automatic recommendations on this one): https://neural-reckoning.github.io/nmc3_provisional_schedule/ Please pass this message on to anyone or any list you think would be interested. Many thanks, The Neuromatch organisers -------------- next part -------------- An HTML attachment was scrubbed... URL: From habesm at gmail.com Sun Oct 25 14:07:14 2020 From: habesm at gmail.com (Mohamad Habes) Date: Sun, 25 Oct 2020 13:07:14 -0500 Subject: Connectionists: Postdoctoral Fellow (University of Texas Health San Antonio) Message-ID: *Postdoctoral Fellow (University of Texas Health San Antonio)* Are you excited about deep learning and transfer learning? Do you want to apply and develop deep learning methods to high dimensional neuroimaging data and make new discoveries which could advance our understanding of Alzheimer?s disease? We are looking for a postdoctoral fellow who is willing to research more deep and transfer learning methods in large cohort based studies. Alzheimer?s disease and other dementias are heterogeneous conditions, which makes differentiating between them and their subtypes very challenging. Our goal is to use neuroimaging data and deep learning to help uncover and detect specific pathologies and patterns emerging in early Alzheimer?s disease. In this position your challenge will be to develop new deep learning architectures and algorithms that allow current pathology detection and prediction of possible future disease trajectories. Your work environment will be the Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC). We build advanced neuroimage analytical techniques to derive discovery. Data-driven approaches are of special interest in our lab, as machine learning and machine intelligence will guide the scientist towards the finding. On broader goal, our tools help delivering precise diagnostics on an individual?s level and ultimately could guide treatment progress. We are part of the Biggs Institute (https://biggsinstitute.org), which is being established as a flagship, free-standing institute within University of Texas Health San Antonio (UTHSA), with the mission of establishing an interdisciplinary, integrated program to provide comprehensive clinical care and undertake innovative and important research into the prevention and treatment of Alzheimer?s Disease and other neurodegenerative conditions, including vascular contributions to dementia, Parkinson?s disease and frontotemporal dementia. It has strong institutional and community support and will benefit from existing resources within UTHSA such as the Barshop Institute for Longevity and Aging Studies, the Center for Biomedical Neuroscience, the School of Nursing, the Cancer Center, and the Research Imaging Institute along with the San Antonio campus of the UT Health Houston School of Public Health. *Responsibilities* ? Develop, test and validate novel architectures and algorithms for deep (transfer) learning with neuroimaging data ? Apply your validated methods to large scale research and real life everyday clinical routine neuroimaging data ? Willingness to work in teams, within NAL, BINC and Biggs and with national and international collaborators ? Communicate your research results to the larger communities through publications in international conferences and journals ? Work with great deal of independence in achieving research goals *Requirements* ? A PhD degree in Artificial Intelligence, Machine Learning, Computer Vision or Medical Image Analytics with solid experience in deep learning; Experience in Neuroimaging and Dementia Research is a plus. ? Great eagerness to solve scientific problems ? Strong programming skills, e.g. in Python, R, C++ and Java. Experience with Python deep learning toolboxes and high-performance computational facilities could be a plus; ? Excellent record of publishing in relevant high-quality journals in the above fields ? Excellent communication abilities in English; spoken and written. If interested, please send a copy of your CV to Dr. Habes (habes at uthscsa.edu ) ---- Mohamad Habes, Ph.D. Assistant Professor, Departments of Radiology and Epidemiology Director, Neuroimage Analytics Laboratory (NAL) Director, Biggs Institute Neuroimaging Core (BINC) Glenn Biggs Institute for Alzheimer?s & Neurodegenerative Diseases Director, Biomedical Image Analytics Division (BIAD) Research Imaging Institute University of Texas Health Science Center San Antonio (UTHSCSA) 7703 Floyd Curl Drive, San Antonio, Texas 78229 (Phone) +1 210-450-8416 (Email) habes at uthscsa.edu -------------- next part -------------- An HTML attachment was scrubbed... URL: From zitao.jerry.liu at gmail.com Sun Oct 25 10:59:09 2020 From: zitao.jerry.liu at gmail.com (Zitao Liu) Date: Sun, 25 Oct 2020 22:59:09 +0800 Subject: Connectionists: Call for Papers - AAAI2021 Spring Symposium on Artificial Intelligence for K-12 Education Message-ID: ** Call for Papers ** - AAAI2021 Spring Symposium on Artificial Intelligence for K-12 Education http://ai4ed.cc/workshops/aaai2021sss The increasingly digitized education tools and the popularity of online learning have produced an unprecedented amount of data that provides us with invaluable opportunities for applying AI in K-12 education. Recent years have witnessed growing efforts from the AI research community devoted to advancing our education and promising results have been obtained in solving various critical problems in K-12 education. Despite gratifying achievements have demonstrated the great potential and bright development prospect of introducing AI in K-12 education, developing and applying AI technologies to educational practice is fraught with its unique challenges, including, but not limited to, extreme data sparsity, lack of labeled data, and privacy issues. Hence, this symposium will focus on introducing research progress on applying AI to K-12 education and discussing recent advances of handling challenges encountered in AI educational practice. --------------------- Symposium Topics --------------------- We encourage paper submissions on a broad range of AI domains for K-12 education. Topics of interest include (in no particular order) but are not limited to following: - Emerging technologies in K-12 education - Evaluation of K-12 education technologies - Immersive learning and multimedia applications - Implications of big data in K-12 education - Self-adaptive learning - Individual and personalized K-12 education - Intelligent learning systems - Intelligent tutoring and monitoring systems - Automatic assessment in K-12 education - Automated grading of assignments - Automated feedback and recommendations - Big data analytics for K-12 education - Analysis of communities of learning - Computer-aided assessment - Course development techniques - Data analytics & big data in K-12 education - Mining and web mining in K-12 education - Learning tools experiences and cases of study - Social media in K-12 education - Smart K-12 education - Digital libraries for learning - K-12 education analytic approaches, methods, and tools - Knowledge management for learning - Learning analytics and K-12 educational data mining - Learning technology for lifelong learning - Tracking learning activities - Uses of multimedia for K-12 education - Wearable computing technology in e-learning - Smart classroom - Dropout prediction - Knowledge tracing --------------------- Paper Submission --------------------- The symposium solicits paper submissions from participants (2?6 pages). Abstracts of the following flavors will be sought: - research ideas - case studies (or deployed projects) - review papers - best practice papers - lessons learned. The format is the standard double-column AAAI Proceedings Style and single blind. The author kit can be found at https://www.aaai.org/Publications/Templates/AuthorKit21.zip. We will encourage submissions of works-in-progress and extended abstracts, in addition to full length papers. All submissions will be peer-reviewed. Some will be selected for spotlight talks, and some for the poster session. The submission website is at https://easychair.org/conferences/?conf=sss21. For more questions about the workshop and submissions, please send email to liuzitao at 100tal.com. --------------------- Important Dates --------------------- - December 15, 2020: Workshop paper submission due (23:59, Pacific Standard Time) - December 31, 2020: Notifications of acceptance - March 22?24, 2021: Symposium Date --------------------- Organizers --------------------- Zitao Liu TAL Education Group, China Jiliang Tang Michigan State University, USA Yi Chang Jilin University, China Xiangen Hu University of Memphis, USA Diane Litman University of Pittsburgh, USA Best Regards, Zitao Liu on behalf of the symposium organizing committees (with Jiliang Tang, Yi Chang, Xiangen Hu, Diane Litman) -- Dr. Zitao Liu | Director of Machine Learning, Head of TAL AI Open Platform | TAL Education Group (NYSE:TAL) | http://www.zitaoliu.com -------------- next part -------------- An HTML attachment was scrubbed... URL: From pjthomas at case.edu Mon Oct 26 09:11:26 2020 From: pjthomas at case.edu (Peter Thomas) Date: Mon, 26 Oct 2020 09:11:26 -0400 Subject: Connectionists: Virtual Workshop on Motor Control October 26-29, 2020 In-Reply-To: References: Message-ID: Dear Colleagues The 2020 virtual workshop on motor control will begin today at 10:00 am US Eastern time. Because the autumnal time change went into effect already in Europe, while it will not happen in the US until next weekend, the time difference is currently only 5 hours, not the usual six. Talks will begin today at 3:00 pm European time. Please find attached a corrected schedule. Sincerely Peter Thomas On Tue, Oct 20, 2020 at 11:00 PM Peter Thomas wrote: > Dear Colleagues > > Together with Hillel Chiel (CWRU) and Silvia Daun (University of Cologne) > I invite you to participate in an online workshop on motor control on > October 26-29, 2020. Topics will span theory and experiment, and systems > ranging from vertebrate to invertebrate, from locomotion to > cardiorespiratory control. Talks begin at 10:00 am US Eastern time. > Please find attached the full schedule. The workshop will be run as a zoom > webinar (access details follow). Talks will be recorded, technology > permitting. Please contact motor-control-workshop-2020 at case.edu with any > questions. > > Sincerely > > Peter Thomas > > Hi there, > > You are invited to a Zoom webinar. > When: Oct 26, 2020 10:00 AM Eastern Time (US and Canada) > Every day, 4 occurrence(s) > Oct 26, 2020 10:00 AM > Oct 27, 2020 10:00 AM > Oct 28, 2020 10:00 AM > Oct 29, 2020 10:00 AM > Please download and import the following iCalendar (.ics) files to > your calendar system. > Daily: > https://cwru.zoom.us/webinar/tJMrdOitrj0iHNAJwd0ZGUJKwk0Agl0O3bdd/ics?icsToken=98tyKuCvqDgrH9STuB-DRowEBIjCd-_ziCFHgo18tgjhUxp0VyndIekSE7VzQPeD > Topic: 2020 Virtual Motor Control Workshop > > Please click the link below to join the webinar: > https://cwru.zoom.us/j/97631506864?pwd=ZG1kZFcvc0hGeE11TGNvNDFnRlJldz09 > Passcode: 817971 > Or iPhone one-tap : > US: +16465588656,,97631506864# or +13017158592,,97631506864# > Or Telephone: > Dial(for higher quality, dial a number based on your current location): > US: +1 646 558 8656 or +1 301 715 8592 or +1 312 626 6799 or +1 > 669 900 6833 or +1 253 215 8782 or +1 346 248 7799 > Webinar ID: 976 3150 6864 > International numbers available: https://cwru.zoom.us/u/aegjtyRjc7 > > Or an H.323/SIP room system: > H.323: > 162.255.37.11 (US West) > 162.255.36.11 (US East) > 221.122.88.195 (China) > 115.114.131.7 (India Mumbai) > 115.114.115.7 (India Hyderabad) > 213.19.144.110 (Amsterdam Netherlands) > 213.244.140.110 (Germany) > 103.122.166.55 (Australia) > 209.9.211.110 (Hong Kong SAR) > 149.137.40.110 (Singapore) > 64.211.144.160 (Brazil) > 69.174.57.160 (Canada) > 207.226.132.110 (Japan) > Meeting ID: 976 3150 6864 > Passcode: 817971 > SIP: 97631506864 at zoomcrc.com > Passcode: 817971 > > > -- > Peter J. Thomas > > Professor > Case Western Reserve University > Department of Mathematics, Applied Mathematics and Statistics. > Co-Editor-in-Chief, *Biological Cybernetics. * > https://link.springer.com/journal/422 > > homepage: http://www.case.edu/math/thomas/ > g-scholar: http://scholar.google.com/citations?user=5ctD7qIAAAAJ > -- Peter J. Thomas Professor Case Western Reserve University Department of Mathematics, Applied Mathematics and Statistics. Co-Editor-in-Chief, *Biological Cybernetics. * https://link.springer.com/journal/422 homepage: http://www.case.edu/math/thomas/ g-scholar: http://scholar.google.com/citations?user=5ctD7qIAAAAJ -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: 2020 Motor Control Workshop - schedule.pdf Type: application/pdf Size: 39289 bytes Desc: not available URL: From habesm at gmail.com Mon Oct 26 13:53:55 2020 From: habesm at gmail.com (Mohamad Habes) Date: Mon, 26 Oct 2020 12:53:55 -0500 Subject: Connectionists: Postdoctoral Fellow Deep Learning (University of Texas Health San Antonio) Message-ID: *Postdoctoral Fellow (University of Texas Health San Antonio)* Are you excited about deep learning and transfer learning? Do you want to apply and develop deep learning methods to high dimensional neuroimaging data and make new discoveries which could advance our understanding of Alzheimer?s disease? We are looking for a postdoctoral fellow who is willing to research more deep and transfer learning methods in large cohort based studies. Alzheimer?s disease and other dementias are heterogeneous conditions, which makes differentiating between them and their subtypes very challenging. Our goal is to use neuroimaging data and deep learning to help uncover and detect specific pathologies and patterns emerging in early Alzheimer?s disease. In this position your challenge will be to develop new deep learning architectures and algorithms that allow current pathology detection and prediction of possible future disease trajectories. Your work environment will be the Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC). We build advanced neuroimage analytical techniques to derive discovery. Data-driven approaches are of special interest in our lab, as machine learning and machine intelligence will guide the scientist towards the finding. On broader goal, our tools help delivering precise diagnostics on an individual?s level and ultimately could guide treatment progress. We are part of the Biggs Institute (https://biggsinstitute.org), which is being established as a flagship, free-standing institute within University of Texas Health San Antonio (UTHSA), with the mission of establishing an interdisciplinary, integrated program to provide comprehensive clinical care and undertake innovative and important research into the prevention and treatment of Alzheimer?s Disease and other neurodegenerative conditions, including vascular contributions to dementia, Parkinson?s disease and frontotemporal dementia. It has strong institutional and community support and will benefit from existing resources within UTHSA such as the Barshop Institute for Longevity and Aging Studies, the Center for Biomedical Neuroscience, the School of Nursing, the Cancer Center, and the Research Imaging Institute along with the San Antonio campus of the UT Health Houston School of Public Health. *Responsibilities* ? Develop, test and validate novel architectures and algorithms for deep (transfer) learning with neuroimaging data ? Apply your validated methods to large scale research and real life everyday clinical routine neuroimaging data ? Willingness to work in teams, within NAL, BINC and Biggs and with national and international collaborators ? Communicate your research results to the larger communities through publications in international conferences and journals ? Work with great deal of independence in achieving research goals *Requirements* ? A PhD degree in Artificial Intelligence, Machine Learning, Computer Vision or Medical Image Analytics with solid experience in deep learning; Experience in Neuroimaging and Dementia Research is a plus. ? Great eagerness to solve scientific problems ? Strong programming skills, e.g. in Python, R, C++ and Java. Experience with Python deep learning toolboxes and high-performance computational facilities could be a plus; ? Excellent record of publishing in relevant high-quality journals in the above fields ? Excellent communication abilities in English; spoken and written. If interested, please send a copy of your CV to Dr. Habes (habes at uthscsa.edu ) ---- Mohamad Habes, Ph.D. Assistant Professor, Departments of Radiology and Epidemiology Director, Neuroimage Analytics Laboratory (NAL) Director, Biggs Institute Neuroimaging Core (BINC) Glenn Biggs Institute for Alzheimer?s & Neurodegenerative Diseases Director, Biomedical Image Analytics Division (BIAD) Research Imaging Institute University of Texas Health Science Center San Antonio (UTHSCSA) 7703 Floyd Curl Drive, San Antonio, Texas 78229 (Phone) +1 210-450-8416 (Email) habes at uthscsa.edu -------------- next part -------------- An HTML attachment was scrubbed... URL: From blextar at gmail.com Tue Oct 27 00:35:32 2020 From: blextar at gmail.com (Luca Rossi) Date: Tue, 27 Oct 2020 12:35:32 +0800 Subject: Connectionists: CFP S+SSPR 2020 [Deadline approaching] Message-ID: Dear all, Please consider submitting to S+SSPR 2020 - the submission deadline (1st of November) is approaching. The plain text CFP is listed below and for further information visit https://www.dais.unive.it/sspr2020/. Note that due to the ongoing covid-19 pandemic this edition of S+SSPR will be ONLINE and FREE. Looking forward to your submissions, S+SSPR organising committee === CALL FOR PAPERS IAPR Joint International Workshops on 13th Statistical Techniques in Pattern Recognition (SPR) 18th Structural and Syntactic Pattern Recognition Workshop (SSPR) Time and place: 19-22 January 2021, Online event Paper submission deadline: 1 November 2020 S+SSPR 2020 is a joint event organised by Technical Committee 1 (Statistical Pattern Recognition Technique) and Technical Committee 2 (Structural and Syntactical Pattern Recognition) of the International Association of Pattern Recognition (IAPR). Following the trend of previous editions, S+SSPR 2020 will be held in close proximity to the International Conference on Pattern Recognition (ICPR). Authors are invited to submit papers addressing topics in statistical, structural or syntactic pattern recognition and their applications. Accepted papers will be published in Springer?s Lecture Notes in Computer Science (LNCS) series. For details see: http://www.dais.unive.it/sspr2020/ -- Luca Rossi Lecturer in Artificial Intelligence School of Electronic Engineering and Computer Science Queen Mary University of London https://blextar.github.io/luca-rossi/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From cgf at isep.ipp.pt Mon Oct 26 12:24:22 2020 From: cgf at isep.ipp.pt (Carlos Ferreira) Date: Mon, 26 Oct 2020 16:24:22 +0000 Subject: Connectionists: IEEE/ACM/ASA DSAA'2021: CALL FOR SPECIAL SESSION PROPOSALS Message-ID: ====================================================================== IEEE/ACM/ASA DSAA'2021 CALL FOR SPECIAL SESSION PROPOSALS https://dsaa2021.dcc.fc.up.pt/calls/special-sessions ====================================================================== Important Dates ------------------------------------------------------------------------------ * Special Session Proposal Due:30 November 2020 * Special Session Proposal Notification:15 December 2020 * Special Session Paper Submission Deadline:23 May 2021 * Special Session Paper Notification: 25 July 2021 The DSAA conference series ------------------------------------------------------------------------------ * Strong Research track and Applications track. * Student Poster and Industry Poster sessions highlighting students? research advances and industry?s best practices. * One-day Industry Day with Data Science School for business * Special sessions on the foundations and emerging areas for data science. * Special panel on the trends and controversies of data science and analytics * A strong interdisciplinary research program spanning the areas of data science, including statistics, machine learning, computing, and analytics. * Strong cross-domain interactions among researchers and industry and government policy-makers and practitioners. * Industry and research exhibits. * Technically sponsored and supported by IEEE CIS, ACM SIGKDD and ASA * EI indexed proceedings, hosted at IEEEXplore More on this year?s DSAA:https://dsaa2021.dcc.fc.up.pt About DSAA Special Sessions ------------------------------------------------------------------------------ DSAA Special Sessions are an important part of the main conference program. They bring together researchers, industry experts, practitioners and potential users who are interested in cultivating specialized and important aspects of data science and analytics. DSAA Special Sessions are intended to promote EMERGING data science research areas that are not well established and covered in the main conference tracks, while featuring much higher quality, integrity and impact of presentations than classic workshops typically hosted in all major conferences. The same evaluation criteria and quality level apply as for the main conference, but the papers must adhere to the area of the special session they are submitted to, and the reviewers are experts in that area. Many real world challenges call for interdisciplinary solutions and a dialog of cultures. In DSAA 2021, we particularly encourage proposals for special sessions that promote such a dialog, e.g. on statistics and data mining, pattern recognition and statistics, data mining and simulation. We welcome proposals that promote a more intensive interaction between different communities and proposals that promote cooperation to solve interdisciplinary problems. Proposals on special sessions on how interdisciplinary data science can make the world stronger against disease outbreaks are strongly encouraged. Thus, special sessions might focus on: a) topics on the border of data science research area, b) advanced topics within the data science research area, or c) specific application areas for data science. Special Session Proposal Submission and Review ------------------------------------------------------------------------------ Proposals for hosting special sessions at DSAA 2021 are welcome. The proposals must address: (1) Title (2) Aims and scope (3) Topics of interest (4) Relevance to the DSAA main conference tracks and topics (5) Organizers (6) Past special sessions or relevant experiences or track records (7) Potential committee members (8) Potential invited speakers For each organizer in (5), provide name, affiliation, country, email and a short biographical sketch, describing relevant qualifications and experience; identify at least one organizer as the contact person. For (6), list any special session or relevant events (e.g., workshops) the organizers have organized in recent years in DSAA or other major conferences; for each, list the year, the conference, number of submissions, number of papers accepted, number of participants, etc. For (7), give a list of qualified committee members who would be invited. For (8), please provide the names of one or two authoritative speakers that could open the special session, and that can deliver a comprehensive overview of the topic of interest. Special session proposals will be reviewed based on the above criteria and quality of the proposals as well as their relationship to the main conference topics. Preference may be given to timely topics that are critical for data science and analytics, inspire highly interactive discussions, and showcase the impact of data science and analytics. Proposers are encouraged to give an estimation of the number of submissions they expect. Special Session Organization, Paper Submission and Review ------------------------------------------------------------------------------ Once a special session proposal has been accepted, its organizers should widely publicize the session for calling for papers. Papers for a special sessionshould be submitted to the special session track instead of the main conference, but using the same submission system. Special session papers strictly follow the same specifications, requirements and policies as the main conference submissions in terms of the paper submission deadline, notification deadline, paper formatting and length, and important policies. Reviewing of the submissions in each special session is coordinated by the special session organizers, and is fully aligned to the main conference evaluation process. In particular: * All papers submitted to special sessions will be double-blind reviewed * Organizers of each special session will recommend program committee members(PCMs)to the DSAA Program Chairs and Special SessionsChairs. * Approved PCMs will be invited by the conference Special Session Chairs into the submission system for each Special Session; a reviewer is allowed toserve as PCM in more than one Special Session. * Papers will be assigned to appropriatePCMs by the Special Session organizers for review. * Special Session organizers will make recommendations of acceptance/rejection for papers in their sessions, which will be double-checked by the conference Special Session Chairs. To guarantee uniform quality control for all special sessions and to be consistent with the main conference, the final decisions of special session paper acceptance/rejection are made by the DSAA Program Chairs. Proceedings, Indexing and Special Issues ------------------------------------------------------------------------------ All accepted full-length special session papers will be published by IEEE in the DSAA main conference proceedings under its Special Session scheme. All papers will be submitted for inclusion in the IEEEXplore Digital Library. The conference proceedings will be submitted for EI indexing through INSPEC by IEEE. Organizers of Special Sessionsmay additionally arrange for special issues to further publish the extended journal versions of the papers. Several past special sessions have published special issues with the International Journal of Data Science and Analytics (JDSA, Springer). General Inquiries and Submission ------------------------------------------------------------------------------ Special session proposals should be submitted to the DSAA 2021 Special Session chairs atsessions-dsaa2021 at dsaa.co Specific enquiries about a Special Session should be submitted to the session organizers, who are advised to set up a joint email address, once their proposal is accepted. Carlos Ferreira ISEP | Instituto Superior de Engenharia do Porto Rua Dr. Ant?nio Bernardino de Almeida, 431 4249-015 Porto - PORTUGAL tel. +351 228 340 500 | fax +351 228 321 159 mail at isep.ipp.pt | www.isep.ipp.pt From zuike2013 at outlook.com Mon Oct 26 11:32:23 2020 From: zuike2013 at outlook.com (Zhuo Su) Date: Mon, 26 Oct 2020 15:32:23 +0000 Subject: Connectionists: [CFP] IEEE TPAMI Special Issue on Learning with Fewer Labels in Computer Vision Message-ID: Call for Papers: IEEE TPAMI Special Issue on Learning with Fewer Labels in Computer Vision https://lwflcv.github.io/ The past several years has witnessed an explosion of interest in and a dizzyingly fast development of machine learning, a subfield of artificial intelligence. Foremost among these approaches are Deep Neural Networks (DNNs) that can learn powerful feature representations with multiple levels of abstraction directly from data when large amounts of labeled data are available. One of the core computer vision areas, namely, object classification achieved a significant breakthrough result with a deep convolutional neural network and the large-scale ImageNet dataset, which is arguably what reignited the field of artificial neural networks and triggered the recent revolution in Artificial Intelligence (AI). Nowadays, artificial intelligence has spread over almost all fields of science and technology. Yet, computer vision remains in the heart of these advances when it comes to visual data analysis, offering the biggest big data and enabling advanced AI solutions to be developed. Undoubtedly, DNNs have shown remarkable success in many computer vision tasks, such as recognizing/localizing/segmenting faces, persons, objects, scenes, actions and gestures, and recognizing human expressions, emotions, as well as object relations and interactions in images or videos. Despite a wide range of impressive results, current DNN based methods typically depend on massive amounts of accurately annotated training data to achieve high performance and are brittle in that their performance can degrade severely with small changes in their operating environment. Generally, collecting large scale training datasets is time-consuming, costly, and in many applications even infeasible, as for certain fields only very limited or no examples at all can be gathered (such as visual inspection or medical domain), although for some computer vision tasks large amounts of unlabeled data may be relatively easy to collect, e.g., from the web or via synthesis. Nevertheless, labeling and vetting massive amounts of real-world training data is certainly difficult, expensive, or time-consuming, as it requires the painstaking efforts of experienced human annotators or experts, and in many cases prohibitively costly or impossible due to some reason, such as privacy, safety or ethic issues (e.g., endangered species, drug discovery, medical diagnostics and industrial inspection). DNNs lack the ability of learning from limited exemplars and fast generalizing to new tasks. However, real-word computer vision applications often require models that are able to (a) learn with few annotated samples, and (b) continually adapt to new data without forgetting prior knowledge. By contrast, humans can learn from just one or a handful of examples (i.e., few shot learning), can do very long-term learning, and can form abstract models of a situation and manipulate these models to achieve extreme generalization. As a result, one of the next big challenges in computer vision is to develop learning approaches that are capable of addressing the important shortcomings of existing methods in this regard. Therefore, in order to address the current inefficiency of machine learning, there is pressing need to research methods, (1) to drastically reduce requirements for labeled training data, (2) to significantly reduce the amount of data necessary to adapt models to new environments, and (3) to even use as little labeled training data as people need. Scope of the Special Issue: This special issue focuses on learning with fewer labels for computer vision tasks such as image classification, object detection, semantic segmentation, instance segmentation, and many others and the topics of interest include (but are not limited to) the following areas: -- Self-supervised learning methods -- New methods for few-/zero-shot learning -- Meta-learning methods -- Life-long/continual/incremental learning methods -- Novel domain adaptation methods -- Semi-supervised learning methods -- Weakly-supervised learning methods Priority will be given to papers with high novelty and originality for research papers, and to papers with high potential impact for survey/overview papers. Paper submission and review: Authors need to submit full papers online through the TPAMI site at https://mc.manuscriptcentral.com/tpami-cs selecting the choice that indicates this special issue. Peer reviewing will follow the standard IEEE review process. Full length manuscripts are expected to follow the TPAMI guidelines in https://www.computer.org/tpami-author-information Submission Deadline: Paper Submission Deadline: April 15, 2021. Guest editors: -- Li Liu: li.liu at oulu.fi National University of Defense Technology, China Center for Machine Vision and Signal Analysis (CMVS), University of Oulu, Finland -- Timothy Hospedales: t.hospedales at ed.ac.uk Professor, University of Edinburgh, UK Principal Scientist at Samsung AI Research Centre Alan Turing Institute Fellow -- Yann LeCun: yann at fb.com Silver Professor, New York University, United States VP and Chief AI Scientist at Facebook -- Mingsheng Long: mingsheng at tsinghua.edu.cn Associate Professor, Tsinghua University, China -- Jiebo Luo: jluo at cs.rochester.edu Professor, University of Rochester, United States -- Wanli Ouyang: wanli.ouyang at sydney.edu.au Senior Lecturer, University of Sydney, Australia -- Matti Pietik?inen: matti.pietikainen at oulu.fi Professor (IEEE Fellow), Center for Machine Vision and Signal Analysis University of Oulu (CMVS), Finland -- Tinne Tuytelaars: Tinne.Tuytelaars at esat.kuleuven.be Professor, KU Leuven, Belgium Main Contact: Li Liu Email: li.liu at oulu.fi, dreamliu2010 at gmail.com National University of Defense Technology, China Center for Machine Vision and Signal Analysis (CMVS), University of Oulu, Finland -------------- next part -------------- An HTML attachment was scrubbed... URL: From sepand.haghighi at yahoo.com Mon Oct 26 14:32:02 2020 From: sepand.haghighi at yahoo.com (Sepand Haghighi) Date: Mon, 26 Oct 2020 18:32:02 +0000 (UTC) Subject: Connectionists: PyCM 3.0 released: Machine learning library for confusion matrix statistical analysis References: <500053787.2649312.1603737122973.ref@mail.yahoo.com> Message-ID: <500053787.2649312.1603737122973@mail.yahoo.com> https://github.com/sepandhaghighi/pycm https://www.pycm.ir http://list.pycm.ir - plot_test.py?added?#330 - axes_gen?function added?#330 - add_number_label?function added?#330 - plot?method added?#330 - combine?method added?#326 - matrix_combine?function added?#326 - Document modified - README.md?modified - Example-2 deprecated?#330 - Example-7 deprecated?#330 - Error messages modified Best RegardsSepand Haghighi -------------- next part -------------- An HTML attachment was scrubbed... URL: From marcus.a.brubaker at gmail.com Mon Oct 26 16:55:14 2020 From: marcus.a.brubaker at gmail.com (Marcus Brubaker) Date: Mon, 26 Oct 2020 16:55:14 -0400 Subject: Connectionists: Open Rank AI/ML Tenure Stream Faculty Position at York University, Toronto, Canada Message-ID: York University has an open AI/ML faculty position at York. It is open to all ranks Assistant/Associate/Full Professor. See http://webapps.yorku.ca/academichiringviewer/viewposition.jsp?positionnumber=2083 for more info. Position Rank: Full Time Professorial Stream - Assistant/Associate/Full Professor Discipline/Field: Artificial Intelligence or Machine Learning Home Faculty: Lassonde School of Engineering Home Department/Area/Division: Department of Electrical Engineering and Computer Science Affiliation/Union: YUFA Position Start Date: July 1, 2021 Artificial Intelligence/Machine Learning Department of Electrical Engineering and Computer Science, Lassonde School of Engineering, York University The Department of Electrical Engineering and Computer Science, York University invites highly qualified candidates to apply for a professorial stream tenured or tenure-track appointment in Artificial Intelligence or Machine Learning at an open rank ? Assistant, Associate or Full Professor level, depending on experience ? to commence July 1, 2021. Salary will be commensurate with qualifications and experience. All York University positions are subject to budgetary approval. A PhD in computer science or a closely related field is required, with a demonstrated record of excellence, or promise of excellence (depending on the rank of the appointment), in research and in teaching. Applicants should have a clearly articulated program of research in Artificial Intelligence or Machine Learning, interpreted broadly. Potential areas include, but are not limited to, machine learning theory, computer vision, and natural language processing. The successful candidate will be expected to engage in outstanding, innovative, and externally funded research at the highest level. Candidates must provide evidence of research excellence or promise of research excellence of a recognized international calibre, as demonstrated by, for example: the research statement; a record of publications in significant journals in the field; presentations at major conferences; awards and accolades; and recommendations from referees of high standing. The position will involve graduate teaching and supervision, as well as undergraduate teaching, and the successful candidate must be suitable for prompt appointment to the Faculty of Graduate Studies. Evidence of excellence or promise of excellence in teaching will be provided through means such as: the teaching statement; teaching accomplishments and pedagogical innovations including in high priority areas such as experiential education and technology enhanced learning; teaching evaluations; and letters of reference. The Department of Electrical Engineering and Computer Science at York University is one of the foremost academic and research departments in Canada with more than 60 faculty members, offering a range of undergraduate programs and research-intensive graduate degrees. For further information please visit http://eecs.lassonde.yorku.ca . Established in 2012, the Lassonde School of Engineering, York University offers a broad range of undergraduate and graduate programs to educate multidisciplinary problem solvers, critical thinkers, and entrepreneurs who understand creativity, communications, social responsibility, and cultural diversity. Further information is available at http://lassonde.yorku.ca/ . York University champions new ways of thinking that drive teaching and research excellence. Through cross-disciplinary programming, innovative course design, diverse experiential learning and a supportive community environment, our students receive the education they need to create big ideas that make an impact on the world. Located in Toronto, York is the third largest university in Canada, with a strong community of 53,000 students, 7,000 faculty and administrative staff, and more than 300,000 alumni. York University has a policy on Accommodation in Employment for Persons with Disabilities and is committed to working towards a barrier-free workplace and to expanding the accessibility of the workplace to persons with disabilities. Candidates who require accommodation during the selection process are invited to contact Professor Marcus Brubaker, Chair of the Search Committee at mab at eecs.yorku.ca. York University is an Affirmative Action (AA) employer and strongly values diversity, including gender and sexual diversity, within its community. The AA Program, which applies to women, members of visible minorities (racialized groups), Aboriginal (Indigenous) people and persons with disabilities, can be found at http://acadjobs.info.yorku.ca/ or by calling the AA line at 416-736-5713. Applicants wishing to self-identify as part of York University?s Affirmative Action program can do so by as part of the online application process. All qualified candidates are encouraged to apply; however, Canadian citizens, permanent residents and Indigenous peoples in Canada will be given priority. No application will be considered without a completed mandatory Work Status Declaration form which is included as part of the online application process. You should complete the online application process at https://apply.lassonde.yorku.ca/ . Include a cover letter (indicating position, and the rank you wish to be considered for), a detailed curriculum vitae, statements of contribution to research, teaching, and curriculum development, three sample research publications. We will start reviewing complete applications on November 15, 2020. For full consideration, we need to have received your complete application materials by November 30, 2020. Posting End Date: November 30, 2020 -------------- next part -------------- An HTML attachment was scrubbed... URL: From ioannakoroni at csd.auth.gr Tue Oct 27 04:47:32 2020 From: ioannakoroni at csd.auth.gr (Ioanna Koroni) Date: Tue, 27 Oct 2020 10:47:32 +0200 Subject: Connectionists: Invitation to Fall Short e-course on Drone Vision and Deep Learning, 18-19th November 2020 References: <004001d68ffc$0ab4cd00$201e6700$@csd.auth.gr> Message-ID: <01cd01d6ac3d$cfe5ba50$6fb12ef0$@csd.auth.gr> Dear Drone engineers, scientists and enthusiasts, you are welcomed to register in this Fall Short e-course on Drone (UAV) Vision and Deep Learning with focus on drone vision/perception, imaging, surveillance, infrastructure inspection, media production and cinematography. It will take place on 18-19th November 2020 as an e-course (due to COVID-19 circumstances), hosted by the Aristotle University of Thessaloniki (AUTH), Thessaloniki, Greece, providing a series of live lectures delivered through a tele-education platform. They will be complemented with on line video recorded lectures and lecture pdfs, to facilitate international participants having time difference issues and to enable you to study at own pace. You can also self-assess your CVML knowledge before/after the course by filling appropriate questionnaires (one per lecture). You will be provided programming exercises to improve your CVML programming skills. The short e-course consists of 16 1-hour lectures organized in two parts (one per day): Part A lectures (8 hours) provide an in-depth presentation to drone systems, mission planning/control and imaging. First, an introduction to multiple drone systems is presented. Then, drone mission planning and control is overviewed, to be complemented by a lecture on drone mission simulations. After reviewing image acquisition, camera geometry (mapping the 3D world on a 2D image plane) and camera calibration, stereo and multi-view imaging systems are presented for recovering 3D world geometry from 2D images. This is complemented by Structure from Motion (SfM) towards Simultaneous Localization and Mapping (SLAM) for vehicle and/or target localization and visual object tracking and 3D localization. Finally, drone communications are overviewed, focusing on drone2ground multiple drone LTE communications, notably on multiple source video compression and streaming. Part B lectures (8 hours) provide first an in-depth presentation of drone computational cinematography that are useful in many applications, besides media production. Then, an introduction to neural networks, provides rigorous formulation of the optimization problems for their training, starting with Perceptron. It continues with Multilayer perceptron training through Backpropagation, presenting many related problems, such as over-/under-fitting and generalization. Deep neural networks, notably Convolutional NNs are the core of this domain nowadays and they are overviewed in great detail. Their application on deep learning for object detection is well presented, as it is a very important issue as well, complemented with a presentation of deep semantic image segmentation. As embedded computing is such an important issue, CVML software development tools and their use in drone imaging is overviewed. This part is concluded with an extremely important drone imaging application, notably, UAV infrastructure inspection. You can use the following link for course registration: http://icarus.csd.auth.gr/cvml-for-autonomous-systems/ Lecture topics, sample lecture ppts and videos, self-assessment questionnaires and programming exercises can be found therein. For questions, please contact: Ioanna Koroni > The short course is organized by Prof. I. Pitas, IEEE and EURASIP fellow, Chair of the IEEE SPS Autonomous Systems Initiative, Director of the Artificial Intelligence and Information analysis Lab (AIIA Lab), Aristotle University of Thessaloniki, Greece, Coordinator of the European Horizon2020 R&D project Multidrone. He is ranked 249-top Computer Science and Electronics scientist internationally by Guide2research (2018). He is head of the EC funded AI doctoral school of Horizon2020 EU funded R&D project AI4Media (1 of the 4 in Europe). He has 31600+ citations to his work and h-index 85+. AUTH is ranked 153/182 internationally in Computer Science/Engineering, respectively, in USNews ranking. Relevant links: 1) Prof. I. Pitas: https://scholar.google.gr/citations?user=lWmGADwAAAAJ &hl=el 2) Horizon2020 EU funded R&D project Aerial-Core: https://aerial-core.eu/ 3) Horizon2020 EU funded R&D project Multidrone: https://multidrone.eu/ 4) Horizon2020 EU funded R&D project AI4Media: https://ai4media.eu/ 5) AIIA Lab: https://aiia.csd.auth.gr/ Course description ?Deep Learning and Computer Vision for Autonomous Systems: Focus on drone vision, imaging, surveillance and cinematography? Part A (8 hours) 1. Introduction to multiple drone systems 2. Drone mission planning and control 3. Image acquisition, camera geometry 4. Stereo and Multiview imaging 5. Localization and mapping 6. Object tracking and 3D localization 7. Drone communications 8. Drone mission simulations Part B (8 hours) 1. Drone cinematography 2. Introduction to neural networks, Perceptron 3. Multilayer perceptron. Backpropagation 4. Deep neural networks. Convolutional NNs 5. Deep learning for object/target detection 6. Deep Semantic Image Segmentation 7. CVML software development tools 8. UAV infrastructure inspection Sincerely yours Prof. I. Pitas Director of the Artificial Intelligence and Information analysis Lab (AIIA Lab) Aristotle University of Thessaloniki, Greece Post scriptum: To stay current on CVMl matters, you may want to register to the CVML email list, following instructions in https://lists.auth.gr/sympa/info/cvml -- This email has been checked for viruses by Avast antivirus software. https://www.avast.com/antivirus -------------- next part -------------- An HTML attachment was scrubbed... URL: From leah at labvanced.com Tue Oct 27 05:59:44 2020 From: leah at labvanced.com (Lee Leah) Date: Tue, 27 Oct 2020 10:59:44 +0100 Subject: Connectionists: Labvanced.com New Eye Tracking Algorithm accuracy Message-ID: <7343131603792470@mail.yandex.com> An HTML attachment was scrubbed... URL: From hocine.cherifi at gmail.com Tue Oct 27 06:49:29 2020 From: hocine.cherifi at gmail.com (Hocine Cherifi) Date: Tue, 27 Oct 2020 11:49:29 +0100 Subject: Connectionists: Call for Participation COMPLEX NETWORKS 2020 December 1-3, 2020 Message-ID: *Ninth** International Conference on Complex Networks & Their Applications* http://www.complexnetworks.org *Registration*: https://complexnetworks.org/registration/ COMPLEX NETWORKS 2020 proceeds as an online event with the support of the local organizing committee of Madrid. *Program: *https://easychair.org/smart-program/COMPLEXNETWORKS2020/ *Tutorials:* *November 30, 2020* The main conference is preceded by a half-day tutorial on November 30, 2020. ? David Garcia Complexity Science Hub Vienna Austria ? Mikko Kivel? Aalto University Finland *Keynote Speakers:* ? Leman Akogu Carnegie Mellon University, USA ? Stefano Boccaletti ISC CNR, Italy ? Fosca Giannotti KDD Lab Pisa, Italy ? J?nos Kert?sz Central European University Hungary ? Vito Latora Queen Mary, University of London UK ? Alex ?Sandy? Pentland MIT Media Lab, USA ? Nata?a Pr?ulj Barcelona Supercomputing Center Spain Best regards, and looking forward to seeing you online at COMPLEX NETWORKS 2020. Rosa M. Benito, Hocine Cherifi, Esteban Moro COMPLEX NETWORKS General Chairs Join us at COMPLEX NETWORKS 2020 Madrid Spain *-------------------------* Hocine CHERIFI University of Burgundy Franche-Comt? Deputy Director LIB EA N? 7534 Editor in Chief Applied Network Science Editorial Board member PLOS One , IEEE ACCESS , Scientific Reports , Journal of Imaging , Quality and Quantity , Computational Social Networks , Complex Systems -------------- next part -------------- An HTML attachment was scrubbed... URL: From eduardo.lopez at bitbrain.es Tue Oct 27 09:24:34 2020 From: eduardo.lopez at bitbrain.es (=?UTF-8?Q?Eduardo_L=C3=B3pez=2DLarraz?=) Date: Tue, 27 Oct 2020 14:24:34 +0100 Subject: Connectionists: Job opportunity - Postdoctoral Sleep Researcher at Bitbrain (Zaragoza, Spain) Message-ID: We are looking for a postdoctoral sleep researcher to join Bitbrain and work on an EU-funded neurotechnology research project. The main objective will be to exploit some of the most recent advances in sleep research to develop interventions based on cutting-edge wearable neurotechnology for sleep (and sleep-mediated cognitive processes) improvement. The candidate will join Bitbrain ?s interdisciplinary R&D department of applied neuroscience and neurotechnology and will lead all the R&D activities related to sleep. The candidate will have to: 1) design the R&D strategy of this new area in the company, which will require attending and participating in international events and networks, and 2) design and carry out a feasibility study in sleep improvement using innovative and practical technologies that can be used outside the lab. The position is initially offered for 12 months and includes a relocation and training package. *Requirements*: Sleep expert with a PhD degree in Neuroscience, Psychology, Biomedical Engineering or similar. Strong background in sleep research, understanding of EEG (required) and brain stimulation (desirable). Project management skills. Problem solving and potential of growth. English is required, Spanish is a plus. *We offer*: - Competitive salary. Benefits associated with mobility and family. - Possibility of doing part of the work remotely (to be discussed). - Work-life balance. * Starting date: *01.03.2021 *Application Deadline*: 15.12.2020 More information and application procedure: https://euraxess.ec.europa.eu/jobs/545040 -------------- next part -------------- An HTML attachment was scrubbed... URL: From chiara.boldrini at iit.cnr.it Tue Oct 27 10:13:53 2020 From: chiara.boldrini at iit.cnr.it (Chiara Boldrini) Date: Tue, 27 Oct 2020 15:13:53 +0100 Subject: Connectionists: PMC Special Issue: IoT for Fighting COVID-19 Message-ID: <48663BB7-27FD-4C0E-B7C9-D732CEC4CCA3@iit.cnr.it> ------------------------------------------------------------------------------ CALL FOR PAPERS Elsevier Pervasive and Mobile Computing (PMC) Journal - (2019 IF: 2.725) Special Issue on IoT for Fighting COVID-19 Submission Deadline: November 21st, 2020 https://www.journals.elsevier.com/pervasive-and-mobile-computing/call-for-papers/special-issue-on-iot-for-fighting-covid-19 ------------------------------------------------------------------------------ Throughout history, pandemics have ravaged humanity with plagues and infections that created humanitarian crises, severed social interactions, hindered economic growth, and caused human lives loss. With the most recent COVID-19 outbreak, researchers and practitioners across various domains such as medical and life sciences, economics, and engineering are coming together to put forward solutions to counter such a threat and aid the society in coping with the fallbacks. In the same context, the computing community in general and IoT researchers and practitioners in particular face a challenge about how IoT-based systems can be exploited to fight the COVID-19 pandemic. This special issue aims to find answers to some fundamental questions such as what IoT systems, technologies, and infrastructures can be exploited for data and knowledge-driven management of the pandemics, how IoT can enable innovative and unconventional solutions for mitigating outbreaks (through mechanisms such as context-sensitive contact tracing and symptomatic detection, smart lockdowns, crowd-sensed discovery of the emerging clusters), and how IoT can contribute to increased public awareness and safety, and counter the negative emotional and social impact. This special issue invites technical papers that focus on theoretical and applied research contributions that present original ideas, modeling and simulation results, prototypes, and real-world experiences in the context of IoT for countering pandemics. Interdisciplinary works are most welcome. This special issue will focus on (but will not be limited to) the following topics: * Engineering of IoT Systems to Counter the COVID-19 Pandemic: IoT-driven smart lockdown; context-sensitive contact tracing and symptomatic detection; crowd-sensed identification of the pandemic hotspots; IoT-driven smart health in the time of pandemics; IoT-driven detection of transmission pathways and dose-response effect; data engineering for pandemic IoT systems. * Algorithms for IoT Systems to Counter the COVID-19 Pandemic: Context modeling and reasoning applied to pandemics; activity and well-being recognition for early detection of symptoms and monitoring of disease progression; data mining, machine learning and causal reasoning applied to IoT systems to fight pandemics; social and complex networks of IoT devices during pandemics. * Empirical Research on IoTs to Counter the COVID-19 Pandemic: Industrial findings and experience reports; validation and evaluation research; measurement studies; systematic mapping studies, or systematic literature reviews. * Reference Architectures, Infrastructures, and Tools for IoT Systems to Counter the COVID-19 Pandemic: IoT-driven pandemic management; architectural patterns and styles for pandemic tracing; prototypes and tool support; mobile cloud computing, fog and edge computing; development environments, frameworks, and tools; technological IoT innovations; trust, security, and privacy. * Analytical models of IoT Systems to Counter the COVID-19 Pandemic: performance models of IoT-driven containment and mitigation strategies; analytical studies of required IoT penetration to achieve control of the epidemic; data-driven IoT models and estimation of key parameters to feed into theoretical models. * Application of IoT Systems to Counter the COVID-19 Pandemic: smart healthcare; smart emergency response systems; smart community and crowd management; food security; smart lockers and innovative choice, pack and delivery methods; unconnected infrastructure and IoT systems. * IoT Systems beyond COVID-19: experience reports, applied solutions, frameworks, prototypes, simulations, and validation research to detect, manage, and counter epidemics like Dengue, Ebola, SARS, Zika, etc. Timeline -------- Submission deadline: 21 November 2020 First notification: February 2021 Guest Editors ------------- Chiara Boldrini, Lead Guest Editor IIT-CNR, Italy Aakash Ahmad University of Ha?il, Saudi Arabia & TeraBlu IoT Systems, Pakistan Mahdi Fahmideh University of Wollongong, Australia Rabie Ramadan Cairo University, Egypt & University of Ha?il, Saudi Arabia Mohamed Younis University of Maryland Baltimore County, USA Submission Guidelines --------------------- All submissions have to be prepared according to the Guide for Authors as published in the Journal website at https://www.journals.elsevier.com/pervasive-and-mobile-computing. Authors should select ?VSI: IoT-COVID19?, from the ?Choose Article Type? pull-down menu during the submission process. To ensure that all manuscripts are correctly identified, for consideration by the special issue, the authors should indicate in the cover letter that the manuscript has been submitted for the special issue ?IoT for Fighting COVID-19?. All contributions must not have been previously published or be under consideration for publication elsewhere. A submission based on one or more papers that appeared elsewhere has to comprise major value-added extensions over what appeared previously (at least 40% new material). Authors are requested to attach to the submitted paper their relevant, previously published articles and a summary in the cover letter explaining the enhancements made in the journal version. For further information, please contact the guest editors. From axel.soto at cs.uns.edu.ar Tue Oct 27 20:44:10 2020 From: axel.soto at cs.uns.edu.ar (Axel Soto) Date: Tue, 27 Oct 2020 21:44:10 -0300 Subject: Connectionists: ACM IUI 2021: Call for tutorials - Deadline extended Message-ID: ACM IUI 2021 - CALL FOR TUTORIAL PROPOSALS In conjunction with the 26th International Conference on Intelligent User Interfaces (IUI 2021) College Station, Texas April 13-17, 2021 https://iui.acm.org/2021/ Tutorial CO-CHAIRS Osnat Mokryn, University of Haifa Vijay Rajanna, Sensel Emails: ossimo at gmail.com vijay.drajanna at gmail.com CALL FOR PROPOSALS We are pleased to invite proposals for tutorials to be held in conjunction with the conference. The goal of the tutorials is to provide a venue for presenting research on focused topics of interest and an informal forum to discuss research questions and challenges. Tutorials are designed to provide fundamental knowledge and experience on topics related to intelligent user interfaces, and the intersection between Human-Computer Interaction (HCI) and Artificial Intelligence (AI). Note: We encourage you to contact the chairs with your ideas (emails above), and work together to prepare an exciting proposal. We encourage proposals for a wide range of tutorials, including but not limited to: - "Hands-on" or "project-centric" tutorials around a specific problem or topic. - Tutorials on a specific topic relevant to IUI; for example, methods and approaches in HCI and/or AI, specific techniques or algorithms to develop intelligent user interfaces, etc. Tutorials will be held on the first day of the conference. We invite submissions of proposals for half-day (3 hours) or full-day (6 hours) tutorials. Proposals will be reviewed and evaluated by the tutorial chairs. We encourage you to consider virtual and semi-virtual options for the tutorial in the submission. The organizers of accepted tutorials are responsible for producing a call for participation and publicizing it, such as distributing the call to relevant newsgroups and electronic mailing lists, and especially to potential audiences from outside the IUI conference community. Tutorial organizers are also required to set up their own website with information about the tutorial and the IUI 2021 web site will refer to this website. PROPOSAL FORMAT Tutorial proposals should be maximum 2 pages long and follow the formatting instructions at https://www.acm.org/publications/proceedings-template. Please either use the Word interim template with Libertine fonts downloaded and embedded, or the LaTex sigconf template. The proposals should be organized as follows: - Name and title: A one-word acronym and a full title. - Description of tutorial topic: This description should discuss the relevance of the suggested topic to IUI and its interest for the IUI2021 audience. Include a brief discussion of why and for which audience the tutorial is of particular interest. - Organizer(s): Names, affiliations, emails, and web pages of the organizer(s). Provide a brief description of the background of the organiser(s). Strong proposals normally include organizers who bring differing perspectives on the topic and are actively connected to the communities of potential participants. Also please provide a list of other tutorials organized by the organizers in the past. - Participants: A statement saying how many participants you expect and how you plan to invite participants for the tutorial. If possible, include the names of at least 10 people who have expressed interest to participate in the tutorial. -Tutorial format: A brief description of the format regarding the mix of events or activities, such as teaching activities, hands-on practical exercises, and general discussion. Please also list here any material you will make available to tutorial participants, e.g. slides, access to hardware/software, handouts, etc. - Planned outcomes of the tutorial: What are you hoping to achieve by the end of the tutorial. - Length: Half-day or Full-day. Please submit your proposal via https://new.precisionconference.com/ selecting the IUI 2021 Tutorials track. IMPORTANT DATES Discuss your topic with the workshop and tutorials chairs: ASAP (tutorials2021 at iui.acm.org) Proposals due: Wednesday, 25 November 2020 Reviews Sent: Monday, 15 December 2020 Revised Proposal Submissions: Wednesday, 30 December 2020 Notifications to authors: Tuesday, 14 January 2021 Camera-ready for Tutorial summary: Wednesday, 10 February 2021 Tutorials held: Tuesday, 13 April 2021 From jncor at dei.uc.pt Tue Oct 27 19:55:14 2020 From: jncor at dei.uc.pt (=?UTF-8?Q?Jo=C3=A3o_Nuno_Correia?=) Date: Tue, 27 Oct 2020 23:55:14 +0000 Subject: Connectionists: Deadline Extension - CfP EvoStar 2021 - The Leading European Event on Bio-Inspired Computation - Seville, Spain. 7-9 April 2021 Message-ID: Dear Colleague(s), Below you will find the updated call for papers for EvoStar 2021. Feel free to distribute. Thank you for your time! ------------------------------------------------ Last Call for papers for the EvoStar conference http://www.evostar.org/2021/ Extended Submission Deadline: November 19, 2020 Conference: 7 to 9 April 2021. Venue: Seville, Spain All accepted papers will be printed in the proceedings published by Springer Verlag in the Lecture Notes in Computer Science (LNCS) series. Please distribute (Apologies for cross-posting) ------------------------------------------------ ***************************************** News: - Deadline Extension to 19th of November, 2020. - EvoStar goes Hybrid! The Evostar is planned as a hybrid event (online and onsite) from 7 to 9 April 2021. Authors that have their submitted work accepted can attend the conference either online or on Seville. - The submission link is now open: https://easychair.org/my/conference?conf=evo2021 - Fast track publication in the Evolutionary Computation journal (MIT Press) for EvoCOP2021: Authors nominated for the best paper award at EvoCOP2021 will be invited to submit an extended version of their work for fast track publication in the Evolutionary Computation journal (MIT Press), subject to standard peer-reviewing. Information at: http://www.evostar.org/2021/evocop/ - Special Issue for EvoMUSART2021: Genetic Programming and Evolvable Machines (Q2, IF: 1.78) will publish a Special Issue on ?Evolutionary computation in Art, music & Design? edited by Juan Romero and Penousal Machado. Some authors from EvoMUSART 2021 will be invited to submit a new paper to this Special Issue. Information at: http://www.evostar.org/2021/evomusart/ - EvoApps: Special Sessions: Confirmed Special Sessions: .Applications of Bioinspired techniques on Social Networks .Applications of Deep Bioinspired Algorithms .Applications of Nature-inspired Computing for Sustainability and Development .Evolutionary Computation in Image Analysis, Signal Processing and Pattern Recognition .Evolutionary Machine Learning .Machine Learning and AI in Digital Healthcare and Personalized Medicine .Parallel and Distributed Systems .Soft Computing Applied to Games Information at: http://www.evostar.org/2021/evoapps/ ****************************************** EvoStar comprises four co-located conferences run each spring at different locations throughout Europe. These events arose out of workshops originally developed by EvoNet, the Network of Excellence in Evolutionary Computing, established by the Information Societies Technology Programme of the European Commission, and they represent a continuity of research collaboration stretching back over 20 years. EvoStar is organised by SPECIES, the Society for the Promotion of Evolutionary Computation in Europe and its Surroundings. This non-profit academic society is committed to promoting evolutionary algorithmic thinking, with the inspiration of parallel algorithms derived from natural processes. It provides a forum for information and exchange. The four conferences include: - EuroGP 24th European Conference on Genetic Programming http://www.evostar.org/2021/eurogp/ - EvoApplications 24th European Conference on the Applications of Evolutionary and bio-inspired Computation http://www.evostar.org/2021/evoapps/ - EvoCOP 21st European Conference on Evolutionary Computation in Combinatorial Optimisation http://www.evostar.org/2021/evocop/ - EvoMUSART 10th International Conference (and 15th European event) on Artificial Intelligence in Music, Sound, Art and Design. http://www.evostar.org/2021/evomusart/ *** Important Dates, Venue and Publication *** Submission Deadline: November 19, 2020 Conference: 7 to 9 April, 2021. Venue: Online and Seville, Spain All accepted papers will be printed in the proceedings published by Springer Verlag in the Lecture Notes in Computer Science (LNCS) series. Submission link: https://easychair.org/my/conference?conf=evo2021 Please, check the website for more information: http://www.evostar.org/2021/ And follow us at: Facebook - https://www.facebook.com/evostarconf/ Twitter - https://twitter.com/EvostarConf/ Instagram - https://www.instagram.com/evostarconference/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From xavier.hinaut at inria.fr Tue Oct 27 20:21:38 2020 From: xavier.hinaut at inria.fr (Xavier Hinaut) Date: Wed, 28 Oct 2020 01:21:38 +0100 Subject: Connectionists: SMILES workshop, Nov 2/3: Sensorimotor Interaction, Language and Embodiment of Symbols In-Reply-To: References: <5d4afc96011b44fd8d6a6a19c51cba5a@ac3e.cl> <733A2658-E810-4264-B479-F728088E63BB@inria.fr> <2794045E-DC0D-4349-8002-2780809CCF23@gmail.com> <18F7C3A3-5E45-4668-893D-4875C15A3531@inria.fr> <3C8BDD1D-CB33-4D46-977D-AFFC91779A28@inria.fr> <090EF4B3-8B59-4A20-8BD8-6148DC3B205C@inria.fr> Message-ID: * WHAT The SMILES workshop is about Sensorimotor Interaction, Language and Embodiment of Symbols. It is a satellite event from the ICDL 2020 (International Conference on Developmental Learning). * WHEN Monday 2nd & Tuesday 3rd November 2020 afternoons from 1pm to 6pm CET (UTC+1) * WHERE Online event on Zoom. (Link sent to registered people the day before, see * LINKS section) * WHO - 6 Invited speakers: - Luc Steels - Jun Tani - Rahma Chaabouni - Leila Wehbe - Emre Ugur - Jean-R?mi King - 6 Selected talks: - Alex Pitti, Cergy-Pontoise, France - Xueyang Yao, Waterloo, Canada - Valentin Villecroze, Bordeaux, France - Wei Hong Chin, Tokyo, Japan - Martin Takac, Bratislava, Slovakia - Alistair Knott, Dunedin, New Zealand * LINKS - ** Website **: https://sites.google.com/view/smiles-workshop/home - ** Registration **: https://forms.gle/4cdHvvm79NcWwnD36 - Contact: smiles.conf at gmail.com - ICDL conference website: https://cdstc.gitlab.io/icdl-2020/ * WHAT+ (Short Description) On the one hand, models of sensorimotor interaction are embodied in the environment and in the interaction with other agents. On the other hand, recent Deep Learning development of Natural Language Processing (NLP) models allow to capture increasing language complexity (e.g. compositional representations, word embedding, long term dependencies). However, those NLP models are disembodied in the sense that they are learned from static datasets of text or speech. How can we bridge the gap from low-level sensorimotor interaction to high-level compositional symbolic communication? The SMILES workshop will address this issue through an interdisciplinary approach involving researchers from (but not limited to): - Sensori-motor learning, - Emergent communication in multi-agent systems, - Chunking of perceptuo-motor gestures (gestures in a general sense: motor, vocal, ...), - Sensori-motor learning, - Symbol grounding and symbol emergence, - Compositional representations for communication and action sequence, - Hierarchical representations of temporal information, - Language processing and acquisition in brains and machines, - Models of animal communication, - Understanding composition and temporal processing in neural network models, and - Enaction, active perception, perception-action loop. Xavier Hinaut, on behalf of the SMILES workshop organisers - Xavier Hinaut, Inria, Bordeaux, France - Cl?ment Moulin-Frier, Inria and Ensta ParisTech, Bordeaux, France - Silvia Pagliarini, Inria, Bordeaux, France - Chukiong Loo, University of Malaya, Kuala Lumpur, Malaysia - Michael Spranger, Sony AI and Sony CSL, Tokyo, Japan - Tadahiro Taniguchi, Ritsumeikan University, Kyoto, Japan - Junpei Zhong, Nottingham Trent University, Nottingham, United Kingdom Xavier Hinaut Inria Researcher (CR) Mnemosyne team, Inria LaBRI, Universit? de Bordeaux Institut des Maladies Neurod?g?n?ratives www.xavierhinaut.com From john.murray at yale.edu Wed Oct 28 03:53:27 2020 From: john.murray at yale.edu (Murray, John) Date: Wed, 28 Oct 2020 07:53:27 +0000 Subject: Connectionists: Postdoctoral Swartz Fellowship Positions in Theoretical and Computational Neuroscience at Yale University Message-ID: Postdoctoral Swartz Fellowship Positions in Theoretical and Computational Neuroscience at Yale University The Swartz Center for Theoretical Neurobiology at Yale University invites applications for up to two postdoctoral positions in Theoretical and Computational Neuroscience, with flexible start date in 2021. Competitive candidates include those with a strong quantitative background who wish to gain neuroscience research experience. We especially encourage candidates with an interest in collaborating directly with experimental neuroscientists. The candidates will be expected to perform theoretical/computational studies relevant to one or more laboratories of the Swartz Center at Yale (for a list of affiliated faculty, see: https://medicine.yale.edu/neuroscience/swartz/corelabs.aspx) and will be encouraged to participate in an expanding quantitative biology environment at Yale. Candidates must hold a Ph.D. or equivalent degree by the time of beginning the fellowship. Please send a CV, selected (p)reprints, contact information for two or three references, and a statement of research interests including which laboratories at Yale are of interest. All application materials should be sent electronically to the following e-mail address: john.murray at yale.edu. Applications will be reviewed as they are received, but priority will be given to those received on or before January 15, 2021. For any questions, please contact John Murray. Yale University is an affirmative action/equal opportunity employer. Yale values diversity in its faculty, students, and staff and especially welcomes applications from women and underrepresented minorities. https://neurojobs.sfn.org/job/27534/postdoctoral-swartz-fellowship-positions-in-theoretical-and-computational-neuroscience-at-yale/ John D. Murray ----------------------------------------------- Assistant Professor of Psychiatry, Physics, and Neuroscience Yale University murraylab.yale.edu ----------------------------------------------- -------------- next part -------------- An HTML attachment was scrubbed... URL: From antona at alleninstitute.org Tue Oct 27 20:09:11 2020 From: antona at alleninstitute.org (Anton Arkhipov) Date: Wed, 28 Oct 2020 00:09:11 +0000 Subject: Connectionists: Scientist I - Bio-realistic Modeling of Reconstructed Cortical Tissue Message-ID: <059A2593-A225-488C-8EF8-655EC75242BC@contoso.com> Scientist I - Bio-realistic Modeling of Reconstructed Cortical Tissue https://alleninstitute.hrmdirect.com/employment/job-opening.php?req=1415274 Our mission at the Allen Institute is to advance our understanding of how the brain works in health and disease. Using a team science approach, we strive to discover how the brain implements fundamental computations through the integration of technological innovation, cutting-edge experiments, modeling, and theory. The Allen Institute is seeking exceptional candidates for a BRAIN Initiative-funded position of Scientist in our Seattle-based multidisciplinary organization. The Scientist will join the computational team of Anton Arkhipov and will focus on data analysis and modeling of structure, activity, and computations in mouse cortical circuits. This project will take advantage of unprecedented experimental datasets from the Allen Institute that contain a systematic characterization of synaptic connections between the cell types (https://portal.brain-map.org/explore/connectivity/synaptic-physiology) and a connectome of individual neurons coupled with dense recordings of activity in the mouse visual cortex (https://microns-explorer.org). The Scientist will work collaboratively with colleagues to integrate these data into new, highly realistic network models of cortical circuits, use the models to explore theoretical predictions, and provide them as a resource to fuel future theoretical, modeling, and experimental work in the community. Our computational team collaborates closely with experimentalists to build systematic classifications of structure and function of the mouse visual cortex based on high-throughput recordings in vitro (e.g., Gouwens et al., Nature Neurosci., 2019; Gouwens et al., Cell, in press, 2020, https://doi.org/10.1101/2020.02.03.932244) and in vivo (e.g., Siegle et al., Nature, in press, 2020, https://doi.org/10.1101/805010). Using systematically constructed models of neurons from diverse types, we are building and simulating data-driven, highly realistic models of the mouse visual cortex (Arkhipov et al., PLOS Comp. Bio., 2018; Billeh et al., Neuron, 2020; https://portal.brain-map.org/explore/models). The team also develops and disseminates modeling software (https://alleninstitute.github.io/bmtk/; https://github.com/AllenInstitute/sonata). Join us to analyze world-class experimental data and build the next generation of brain models! Essential Functions * Collaborate with in-house experimentalists to analyze data from the synaptic physiology and 2-photon calcium imaging/electron microscopy connectomics datasets. * Use these data to build and simulate models of cortical circuits, in order to study mechanisms connecting circuit structure and function. * Publish/present findings in peer-reviewed journals/scientific conferences. Required Education and Experience * PhD degree in Neuroscience, Physics, Applied Mathematics, or related fields. * 0-2 years of post-doctoral experience. * Strong publication record. * Track record of scientific excellence and independent thinking. Preferred Education and Experience * Experience in computational neuroscience and/or systems neuroscience is preferred, but other strong applicants will be considered (with background in computational physics, biophysics, and related disciplines). * Candidates with strong background in experimental systems neuroscience, willing to switch to computational work, are encouraged to apply. * Experience with scientific programming (e.g., in Python) and sharing/collaborative development of software (e.g., GitHub) is a plus. Physical Demands * Fine motor movements in fingers/hands to operate computers and other office equipment; lab equipment Position Type/Expected Hours of Work * This role is currently able to work remotely due to COVID-19 and our focus on employee safety; this may change, and you may be required to work onsite at our South Lake Union office as safety restrictions are lifted in relation to COVID-19. It is the policy of the Allen Institute to provide equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, the Allen Institute will provide reasonable accommodations for qualified individuals with disabilities. Apply here: https://alleninstitute.hrmdirect.com/employment/job-opening.php?req=1415274 -------------- next part -------------- An HTML attachment was scrubbed... URL: From R.Borisyuk at plymouth.ac.uk Wed Oct 28 08:15:38 2020 From: R.Borisyuk at plymouth.ac.uk (Roman Borisyuk) Date: Wed, 28 Oct 2020 12:15:38 +0000 Subject: Connectionists: Ph Position, University of Exeter, UK Message-ID: The University of Exeter is recruiting a PhD student to work on an exciting project to investigate theoretically how neural networks can dynamically transition between multiple behaviours. This BBSRC-funded project is open to students from Mathematics, Physics, Natural Sciences, and Computer Science. The successful candidate will develop new neural network models of rhythmic activity in the tadpole spinal cord. They will use these models to analyse how network behaviour adapts to different sensory inputs. Data for model development will be provided by world-class electrophysiologists, who will also test predictions made by the model. This project will uncover cellular-level and network-level mechanisms that enable dynamic circuit reconfiguration in response to a changing environment. For more information on the project and instructions for applying, please visit http://www.exeter.ac.uk/studying/funding/award/?id=3975. Please contact the project investigators with any question: Jo?l Tabak j.tabak at exeter.ac.uk Roman Borisyuk r.m.borisyuk at exeter.ac.uk ________________________________ [http://www.plymouth.ac.uk/images/email_footer.gif] This email and any files with it are confidential and intended solely for the use of the recipient to whom it is addressed. If you are not the intended recipient then copying, distribution or other use of the information contained is strictly prohibited and you should not rely on it. If you have received this email in error please let the sender know immediately and delete it from your system(s). Internet emails are not necessarily secure. While we take every care, University of Plymouth accepts no responsibility for viruses and it is your responsibility to scan emails and their attachments. University of Plymouth does not accept responsibility for any changes made after it was sent. Nothing in this email or its attachments constitutes an order for goods or services unless accompanied by an official order form. -------------- next part -------------- An HTML attachment was scrubbed... URL: From katagres at gmail.com Wed Oct 28 10:15:05 2020 From: katagres at gmail.com (Kat Agres) Date: Wed, 28 Oct 2020 22:15:05 +0800 Subject: Connectionists: Postdoctoral Research Fellow in Musical BCI available at the National University of Singapore Message-ID: POSTDOCTORAL RESEARCH POSITION AVAILABLE The YST Conservatory of Music at the National University of Singapore (NUS), a world-class, top-ranked university, is seeking a full-time Postdoctoral Research Fellow in Musical Brain Computer Interface (BCI) technology. *Job description* The Research Fellow (RF) will engage in research and development of a music-based Brain Computer Interface (BCI) system for emotion regulation in listeners. She/he will work in a multi-disciplinary team with both technical and clinical scientists to help develop 1) machine learning algorithms, 2) an automatic music generation system for affective music generation, and 3) a Brain-Computer Interface system for emotion mediation to be tested in healthy as well as neurological and mental health patients. The RF will help design and manage user tests and clinical trials, help coordinate research activities and supervise research staff/students in the team, and perform data analyses. The RF will need to be capable of working both independently and in a team, of developing innovative solutions, and of publishing research findings in high-impact conferences and journals. This position is part of a large-scale, 4-year project that aims to create a holistic BCI solution for the restoration and enhancement of brain functions. *Responsibilities* ? Develop novel algorithms for BCI systems for emotion mediation. ? Design solutions for music and BCI-driven therapy for mental health (depression, anxiety). ? Co-develop automatic music generation algorithms. ? Design and develop experiment interfaces, conduct pilot trials and help with clinical integration. ? Data analysis and interpretability of the patients? neural signals. ? Prepare manuscripts and publish in high-impact journals and conferences. ? Assist in supervising research staff and students. ? Participate in IRB applications and report writing. *Requirements* Successful candidates will have: ? Ph.D. in Computer Science & Engineering, Electrical Engineering, or related disciplines ? Experience in Brain-Computer Interface and machine learning is required ? Strong analytical and programming skills ? Knowledge of music ? Strong publication track record ? Strong ability to work independently and in teams ? Experience with algorithmic music or automatic music generation a plus ? Computational neuroscience and neuroimaging experience a plus *Key details* ? Position available immediately ? 3-year contract extendable for 1 year ? Competitive salary and benefits ? The candidate must be based in, or be able to relocate to, Singapore For best consideration, applications should be received by *1 December 2020* . For enquiries and expressions of interest in the position, please contact Asst. Prof. Kat Agres at katagres at nus.edu.sg -- *Kat Agres, Ph.D.* *Assistant Professor, National University of Singapore (NUS)* *Yong Siew Toh Conservatory of Music* 3 Conservatory Drive, Singapore 117376 | Tel: (65) 6601 2956 -------------- next part -------------- An HTML attachment was scrubbed... URL: From contact at sscc.fr Wed Oct 28 10:34:36 2020 From: contact at sscc.fr (SSCC 2020) Date: Wed, 28 Oct 2020 15:34:36 +0100 (CET) Subject: Connectionists: Symposium on Solutions for Smart Cities Challenges (SSCC 2020-Online) Message-ID: <745749575.30602.1603895676280@email.ionos.fr> An HTML attachment was scrubbed... URL: From contact at sscc.fr Wed Oct 28 10:42:14 2020 From: contact at sscc.fr (SSCC 2020) Date: Wed, 28 Oct 2020 15:42:14 +0100 (CET) Subject: Connectionists: CFP-SSCC 2020 :Online Conference - Deadline Nov. 15th In-Reply-To: <2017361011.39744.1603895779157@email.ionos.fr> References: <1594671022.759783.1603506462900@email.ionos.fr> <1659575027.759785.1603506876450@email.ionos.fr> <2017361011.39744.1603895779157@email.ionos.fr> Message-ID: <1609989062.31134.1603896134776@email.ionos.fr> An HTML attachment was scrubbed... URL: From michal.rafal.zareba at gmail.com Wed Oct 28 14:50:00 2020 From: michal.rafal.zareba at gmail.com (=?UTF-8?B?TWljaGHFgiBaYXLEmWJh?=) Date: Wed, 28 Oct 2020 19:50:00 +0100 Subject: Connectionists: NEURONUS 2020 IBRO Neuroscience Forum - registration open 3 more days! Message-ID: *REGISTRATION for NEURONUS 2020 IBRO Neuroscience Forum (8-11 December 2020, ONLINE) is open only for THREE MORE DAYS! The fee has been reduced to 12?. **More information and registration forms can be found on our website: **http://neuronusforum.pl/* *.* The program of the conference consists of numerous sessions on biological, cognitive, computational and medical aspects of neuroscience, creating a dynamic environment for sharing knowledge. The schedule of the meeting is further complemented with lectures by invited guests. This year?s keynote speakers include: - *Karl Friston *(University College London, the UK) - *Pico Caroni *(University of Basel, Switzerland) - *Karin Roelofs *(Radboud University Nijmegen, the Netherlands) - *Alejandro Schinder *(Leloir Institute, Buenos Aires, Argentina) - *Adam Hampshire *(Imperial College London, the UK) - *Dayu Lin *(New York University School of Medicine, the USA) Furthermore, a special panel concerning the Future of Neuroscience will be held. We have confirmed participation of three pioneering researchers: - *Viktor Jirsa *(Aix-Marseille University, France) - *Panayiota Poirazi* (Institute of Molecular Biology and Biotechnology, Heraklion, Greece) - *Dominik Paquet *(Ludwig Maximilian University of Munich, Germany) During the upcoming 11th edition of the conference, we will traditionally continue to put *emphasis on development of early-career researchers*. The main purpose of this event is to provide means for both young and experienced neuroscientists to share the latest discoveries, knowledge and experience in neuroscience, as well as make valuable contacts with scientists representing various fields of neurobiology. We actively promote young scientists through preferentially allocating oral presentations of their experimental results. We strongly encourage you to join this special initiative, and hope to see you soon! On behalf of the Organising Committee, Micha? Zar?ba -------------- next part -------------- An HTML attachment was scrubbed... URL: From iswc.conf at gmail.com Wed Oct 28 19:09:43 2020 From: iswc.conf at gmail.com (International Semantic Web Conference) Date: Thu, 29 Oct 2020 00:09:43 +0100 Subject: Connectionists: ISWC 2020: Nov 1-6 - Programme and Call for Participation Message-ID: <8B78511C-B16D-4DAE-802C-FB79D7F096F3@gmail.com> The 19th International Semantic Web Conference 2020 (Nov 1 - 6) https://iswc2020.semanticweb.org will proceed as an online event next week (Workshops and Tutorials: Nov 1-2; Main conference: Nov 3-6). The detailed programme is available at: https://iswc2020.semanticweb.org/program/conference/ Don't miss it! Registration: https://iswc2020.semanticweb.org/attending/registration/ Highlights include: Keynotes by: - Kavitha Srinivas (Researcher at IBM Research):?Knowledge graphs ? where do we go from here? - Lawrence Hunter (Prof. at Univ. of Colorado, School of Medicine):?Knowledge-based Biomedical Data Science - Guotong Xie (Chief Healthcare Scientist, Ping An Group):?Transform Healthcare by Combining Knowledge Graph and Deep Learning Technologies Virtual presentations of: - 38 research papers - 21 resources papers - 21 in-use papers and Semantic Web Challenges Doctoral Consortium Posters & Demos sessions Vision track sessions Student engagement & mentoring session Workshops and Tutorials: The main conference is preceded by two full days of Workshops and Tutorials on November 1-2, 2020 (Sun-Mo): WORKSHOPS : - 11th Workshop on Ontology Design and Patterns (WOP 2020) - 4th Workshop on Storing, Querying, and Benchmarking the Web of Data (QuWeDa 2020) - The Semantic Web in Practice: Tools and Pedagogy (PRAXIS) - 6th Workshop on Managing the Evolution and Preservation of the Data Web (MEPDaW 2020) - 3rd International Workshop on Contextualized Knowledge Graphs (CKG 2020) - 13th International Workshop on Scalable Semantic Web Knowledge Base Systems (SSWS2020) - Third International Workshop on Semantic Web Meets Health Data Management (SWH 2020) - Wikidata Workshop - The Sixth International Workshop on Natural Language Interfaces for the Web of Data (NLIWOD) - 7th International Workshop on Dataset PROFlLing and Search (PROFILES 2020) - VOILA 2020 ? 5th International Workshop on Visualization and Interaction for Ontologies and Linked Data - International Workshop on Artificial Intelligence Technologies for Legal Documents (AI4LEGAL) - The Fifteenth International Workshop on Ontology Matching (OM-2020) - Semantics for Online Misinformation Detection, Monitoring, and Prediction - Harith Alani, Kalina Bontcheva, H. Sofia Pinto, Raphael Troncy and Freddy Lecue - First workshop on Research data* management for linked open science (DaMaLOS) TUTORIALS : - A Data Science Pipeline for Big Linked Earth Observation Data - Scalable RDF Analytics with SANSA - Knowledge Graph Construction using Declarative Mapping Rules - Building Mobile Semantic Web Apps with Punya - Semantic Explainability For All ? SEMEX4ALL - Pattern-based knowledge base construction (OTTR) - SPARQL Endpoints and Web API (SWApi) - Common Sense Knowledge Graphs (CSKGs) - How to build large knowledge graphs efficiently (LKGT) - Shapes applications and tools Note that the deadline to submit your registration is Friday, October 30 at 12:00PM EDT. Looking forward to seeing you online at ISWC 2020! The Organizing Committee of ISWC 2020. -------------- next part -------------- An HTML attachment was scrubbed... URL: From Francesco.Rea at iit.it Thu Oct 29 04:21:26 2020 From: Francesco.Rea at iit.it (Francesco Rea) Date: Thu, 29 Oct 2020 08:21:26 +0000 Subject: Connectionists: =?windows-1252?q?=5Bjobs=5D__Postdoctoral_positio?= =?windows-1252?q?n_in_=93Cognition_for_safety_and_ergonomics_for_human-ro?= =?windows-1252?q?bot_interaction_in_unstructured_workspaces=94_at_Italian?= =?windows-1252?q?_Institute_of_Technology?= Message-ID: <587ed2c6035b43db88c928ed3bd3165d@iit.it> COgNiTive Architecture for Collaborative Technologies Research Line at Istituto Italiano di Tecnologia in Erzelli, Genoa, is seeking to appoint one postdoctoral position focusing on the assessment of engagement with safety and ergonomic work, the design of proactive measures and counter measures for safety preservation, the optimization of ergonomics, design of software infrastructure for social interaction with the mobile and dexterous co-robot. The first goal of the research is redesigning cognition for safety and ergonomics for human-robot collaboration in manufacturing and construction unstructured workspaces. The second goal is to support the design of new multipurpose robotics for collaboration (co-robots) in manufacturing processes. The selected candidate will work with a multidisciplinary consortium of participants to the recently awarded project VOJEXT, Value Of Joint EXperimentation in digital Technologies for manufacturing and construction (H2020 DT-ICT-03-2020, n. 952197). The candidate will work with different robotic platforms for human-robot interaction in manufacturing and construction sites selected together with the consortium and with different sensorial setups specifically designed to assess ergonomics and safety associated with the workers in unstructured manufacturing and constructions settings. Apply online at https://iit.taleo.net/careersection/ex/jobdetail.ftl?lang=en&job=20000042 The research for this postdoctoral position will involve: * Sensing of human working conditions for social, safe and ergonomic based on human-robot collaboration in unstructured manufacturing and construction settings * Design of control systems for mobile robots for Safety in human-robot collaboration * Development of a system improving human-robot social collaboration in unstructured manufacturing and construction sites * Development of a system improving ergonomics and mitigating health and safety risks in open and unstructured environments -------------- next part -------------- An HTML attachment was scrubbed... URL: From ioannakoroni at csd.auth.gr Thu Oct 29 08:23:24 2020 From: ioannakoroni at csd.auth.gr (Ioanna Koroni) Date: Thu, 29 Oct 2020 14:23:24 +0200 Subject: Connectionists: =?utf-8?q?CfP_1st_Autonomous_Vehicle_Vision_=28AV?= =?utf-8?q?Vision=E2=80=9921=29_Workshop_=28In_conjunction_with_WAC?= =?utf-8?q?V_2021=29?= References: <00d501d6ab6e$a69c1f10$f3d45d30$@csd.auth.gr> Message-ID: <074e01d6adee$4c9abf80$e5d03e80$@csd.auth.gr> Call for Papers 1st Autonomous Vehicle Vision (AVVision?21) Workshop In conjunction with WACV 2021 [Regular Paper Submission Deadline Extended!] The Autonomous Vehicle Vision 2021 (AVVision?21) workshop (webpage: avvision.xyz) aims to bring together industry professionals and academics to brainstorm and exchange ideas on the advancement of visual environment perception for autonomous driving. In this one-day workshop, we will have regular paper presentations and invited speakers to present the state of the art as well as the challenges in autonomous driving. Furthemore, we have prepared several large-scale, synthetic and real-world datasets, which have been annotated by the HKUST, UDI, CalmCar, ATG Robotics, etc. Based on these datasets, three challenges will be hosted to understand the current status of computer vision and machine/deep learning algorithms in solving the visual environment perception problems for autonomous driving: 1) CalmCar MTMC Tracking Challenge, 2) HKUST-UDI UDA Challenge, and 3) KITTI Object Detection Challenge. Keynote Speakers: * Andreas Geiger, University of T?bingen * Ioannis Pitas, Aristotle University of Thessaloniki * Nemanja Djuric, Uber ATG * Walterio Mayol-Cuevas, University of Bristol & Amazon Call for Papers: With a number of breakthroughs in autonomous system technology over the past decade, the race to commercialize self-driving cars has become fiercer than ever. The integration of advanced sensing, computer vision, signal/image processing, and machine/deep learning into autonomous vehicles enables them to perceive the environment intelligently and navigate safely. Autonomous driving is required to ensure safe, reliable, and efficient automated mobility in complex uncontrolled real-world environments. Various applications range from automated transportation and farming to public safety and environment exploration. Visual perception is a critical component of autonomous driving. Enabling technologies include: a) affordable sensors that can acquire useful data under varying environmental conditions, b) reliable simultaneous localization and mapping, c) machine learning that can effectively handle varying real-world conditions and unforeseen events, as well as ?machine-learning friendly? signal processing to enable more effective classification and decision making, d) hardware and software co-design for efficient real-time performance, e) resilient and robust platforms that can withstand adversarial attacks and failures, and f) end-to-end system integration of sensing, computer vision, signal/image processing and machine/deep learning. The AVVision'21 workshop will cover all these topics. Research papers are solicited in, but not limited to, the following topics: * 3D road/environment reconstruction and understanding; * Mapping and localization for autonomous cars; * Semantic/instance driving scene segmentation and semantic mapping; * Self-supervised/unsupervised visual environment perception; * Car/pedestrian/object/obstacle detection/tracking and 3D localization; * Car/license plate/road sign detection and recognition; * Driver status monitoring and human-car interfaces; * Deep/machine learning and image analysis for car perception; * Adversarial domain adaptation for autonomous driving; * On-board embedded visual perception systems; * Bio-inspired vision sensing for car perception; * Real-time deep learning inference. Author Guidelines: Authors are encouraged to submit high-quality, original (i.e. not been previously published or accepted for publication in substantially similar form in any peer-reviewed venue including journal, conference or workshop) research. The paper template is identical to the WACV2020 main conference. The author toolkit (latex only) is available both on Overleaf (https://www.overleaf.com/latex/templates/wacv-2021-author-kit-template/ndrtfkktpxjx) and in Github (https://github.com/wacv2021/WACV-2021-Author-Kit). The submissions are handled through the CMT submission website: https://cmt3.research.microsoft.com/AVV2021/. Papers presented at the WACV workshops will be published as part of the "WACV Workshops Proceedings" and should, therefore, follow the same presentation guideliness as the main conference. Workshop papers will be included in IEEE Xplore, but will be indexed separatelly from the WACV main conference papers. For questions/remarks regarding the submission e-mail: avv.workshop at gmail.com . Challenges: Challenge 1: CalmCar MTMC Tracking Challenge Multi-target multi-camera (MTMC) tracking systems can automatically track multiple vehicles using an array of cameras. In this challenge, participants are required to design robust MTMC Tracking algorithms, which are targeted at vehicles, where the same vehicles captured by different cameras possess the same tracking IDs. The competitors will have access to four large-scale training datasets, each of which includes around 1200 annotated RGB images, where the labels cover the types of vehicles, tracking IDs and 2D bounding boxes. Identification precision (IDP) and identification recall (IDR) will be used as metrics to evaluate the performance of the implemented algorithms. The competitors are required to submit their pretrained models as well as the corresponding docker image files via the CMT submission system (https://cmt3.research.microsoft.com/AVV2021/) for algorithm evaluation (in terms of both speed and accuracy). The winner of the competition will receive a monetary prize (US$5000) and will give a keynote presentation at the workshop. Challenge 2: HKUST-UDI UDA Challenge Deep neural networks excel at learning from large amounts of data but they can be inefficient when it comes to generalizing and applying learned knowledge to new datasets or environments. In this competition, participants need to develop an unsupervised domain adaptation (UDA) framework which can allow a model trained on a large synthetic dataset to generalize to real-world imagery. The tasks in this competition include: 1) UDA for monocular depth prediction and 2) UDA for semantic driving-scene segmentation. The competitors will have access to Ready to Drive (R2D) dataset, which is a large-scale synthetic driving scene dataset collected under different weather/illumination conditions using the Carla Simulator. In addition, competitors will also have access to a small amount of real-world data. The mean absolute value of the relative (mAbsRel) error and the mean intersection over union (mIoU) score will be used as metrics to evaluate the performance of UDA for monocular depth prediction and UDA for semantic driving scene segmentation, respectively. The competitors will be required to submit their pretrained models and docker image files via the CMT submission system (https://cmt3.research.microsoft.com/AVV2021/). Challenge 3: KITTI Object Detection Challenge Researchers of top-ranked object detection algorithms submitted to the KITTI Object Detection Benchmarks (http://www.cvlibs.net/datasets/kitti/eval_3dobject.php) will have the opportunity to present their work at AVVision'21, subject to space availability and approval by the workshop organizers. It should be noted that only the algorithms submitted before 12 December 2020 are eligible for presentation at AVVision'21. Important Dates: Full Paper Submission: 08 November 2020 (No extensions!) Notification of Acceptance: 22 November 2020 Camera-Ready Paper Due: 29 November 2020 HKUST-UDI UDA Challenge abstract and code submission: 13 December 2020 Notification of HKUST-UDI UDA Challenge results: 20 December 2020 CalmCar MTMC Tracking Challenge abstract and code submission: 13 December 2020 Notification of CalmCar MTMC Tracking Challenge results: 20 December 2020 Post scriptum: To stay current on CVMl matters, you may want to register to the CVML email list, following instructions in https://lists.auth.gr/sympa/info/cvml -- This email has been checked for viruses by Avast antivirus software. https://www.avast.com/antivirus -------------- next part -------------- An HTML attachment was scrubbed... URL: From beckers at mcmaster.ca Thu Oct 29 09:43:56 2020 From: beckers at mcmaster.ca (Sue Becker) Date: Thu, 29 Oct 2020 09:43:56 -0400 Subject: Connectionists: faculty position in Computational Approaches to Psychology, Neuroscience & Behaviour at McMaster University In-Reply-To: References: , <20201028141709.D464BC34CF@mbx.rhpcs.mcmaster.ca> , <5ea3951889f44e51aab7ee05df2db141@YT1PR01MB3610.CANPRD01.PROD.OUTLOOK.COM> <3a5226591fe843cba65fda1206a45183@YT1PR01MB3610.CANPRD01.PROD.OUTLOOK.COM> <53636812d21285f21380d7b6c7511909@mcmaster.ca> Message-ID: Dear colleagues, We have an open faculty position at the Assistant Professor level in Computational Approaches to Psychology, Neuroscience and Behaviour. The candidate could conduct computational research in a wide range of areas. Please see the the attached job advert and the link below for details. https://careers.mcmaster.ca/psp/prepprd/EMPLOYEE/HRMS/c/HRS_HRAM.HRS_APP_SCHJOB.GBL?Page=HRS_APP_JBPST&Action=U&FOCUS=Applicant&SiteId=1000&JobOpeningId=34946&PostingSeq=1 Please feel free to share this with others who may be interested. thanks and best wishes, Sue --- Sue Becker, Professor Neurotechnology and Neuroplasticity Lab, PI Dept. of Psychology Neuroscience & Behaviour, McMaster University www.science.mcmaster.ca/pnb/department/becker [1] Links: ------ [1] http://www.science.mcmaster.ca/pnb/department/becker -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: McMaster PNB Computational Job Ad.pdf Type: application/pdf Size: 132571 bytes Desc: not available URL: From marinella.petrocchi at iit.cnr.it Thu Oct 29 09:21:56 2020 From: marinella.petrocchi at iit.cnr.it (Marinella Petrocchi) Date: Thu, 29 Oct 2020 14:21:56 +0100 Subject: Connectionists: 1st CfP -- ACM Symposium on Access Control Models and Technologies -- SACMAT 2021 Message-ID: Apologies for cross-posting ACM Symposium on Access Control Models and Technologies -- SACMAT 2021 June 16-18, 2012, Barcelona, Spain http://sacmat.dista.uninsubria.it/2021/about.php ---------------------------------------------------------- Important dates ---------------------------------------------------------- * Paper submission: February 15, 2021 (11:59 pm AOE) * Rebuttal: March 30 - April 2nd, 2021 * Notifications: April 15th, 2021 * Systems demo and Poster submissions: April 19th, 2021 * Systems demo and Poster notifications: April 27th, 2021 * Panel Proposal: TBD * Camera ready: May 4th, 2021 * Conference date: June 16 ? June 18, 2021 * Call for Research Papers Papers offering novel research contributions are solicited for submission. Accepted papers will be presented at the symposium and published by the ACM in the symposium proceedings. In addition to the regular research track, this year SACMAT will again host the special track -- "Blue Sky/Vision Track". Researchers are invited to submit papers describing promising new ideas and challenges of interest to the community as well as access control needs emerging from other fields. We are particularly looking for potentially disruptive and new ideas which can shape the research agenda for the next 10 years. We also encourage submissions to the newly introduced ?Work-in-progress Track? to present ideas that may have not been completely developed and experimentally evaluated. Topics of Interest Submissions to the regular track covering any relevant area of access control and computer security are welcomed. Areas of interest include, but are not limited to, the following: Systems: * Operating systems * Cloud systems and their security * Distributed systems * Fog and Edge-computing systems * Cyber-physical and Embedded systems * Mobile systems * Autonomous systems (e.g., UAV security, autonomous vehicles, ) * IoT systems (e.g., home-automation systems) * WWW Network: * Network systems (e.g., Software-defined network, Network function virtualization) * Corporate and Military-grade Networks * Wireless and Cellular Networks * Opportunistic Network (e.g., delay-tolerant network, P2P) * Overlay Network * Satellite Network Privacy and Privacy-enhancing Technologies: * Mixers and Mixnets * Anonymous protocols (e.g., Tor) * Online social networks (OSN) * Anonymous communication and censorship resistance * Access control and identity management with privacy * Cryptographic tools for privacy * Data protection technologies * Attacks on Privacy and their defenses Authentication: * Password-based Authentication * Biometric-based Authentication * Location-based Authentication * Identity management * Usable authentication Mechanisms: * Blockchain Technologies * AI/ML Technologies * Cryptographic Technologies * Programming-language based Technologies * Hardware-security Technologies (e.g., Intel SGX, ARM TrustZone) * Economic models and game theory * Trust Management * Usable mechanisms Data Security: * Big data * Databases and data management * Data leakage prevention * Data protection on untrusted infrastructure Policies and Models: * Novel policy language design * New Access Control Models * Extension of policy languages * Extension of Models * Analysis of policy languages * Analysis of Models * Policy engineering and policy mining * Verification of policy languages * Efficient enforcement of policies * Usable access control policy * Regular Track Paper Submission and Format Papers must be written in English. Authors are required to use the ACM format for papers, using the two-column SIG Proceedings Template (the sigconf template for LaTex) available in the following link: https://www.acm.org/publications/authors/submissions The length of the paper in the proceedings format must not exceed twelve US letter pages formatted for 8.5" x 11" paper and be no more than 5MB in size. It is the responsibility of the authors to ensure that their submission will print easily on simple default configurations. The submission must be anonymous, so information that might identify the authors - including author names, affiliations, acknowledgements, or obvious self-citations - must be excluded. It is the authors' responsibility to ensure that their anonymity is preserved when citing their own work. Submissions should be made to the EasyChair conference management system by the paper submission deadline of February 15, 2021 11:59 pm AOE: https://easychair.org/conferences/?conf=sacmat21 All submissions must contain a significant original contribution. That is, submitted papers must not substantially overlap papers that have been published or that are simultaneously submitted to a journal, conference, or workshop. In particular, simultaneous submission of the same work is not allowed. Wherever appropriate, relevant related work, including that of the authors, must be cited. Submissions that are not accepted as full papers may be invited to appear as short papers. At least one author from each accepted paper much register for the conference prior to the camera-ready deadline. * Blue Sky Track Paper Submission and Format All submissions to this track should be in the same format as for the regular track, but the length must not exceed ten US letter pages, and the submission are not required to be anonymized (optional). Submissions to this track should be submitted to the EasyChair conference management system by the same deadline as for the regular track. * Work-in-progress Track Paper Submission and Format Authors are invited to submit papers in the newly introduced work-in-progress track. This track is introduced for (junior) authors, ideally Ph.D. and Masters students, to obtain early, constructive feedback on their work. Submissions in this track should follow the same format as for the regular track papers while limiting the total number of pages to six US letter pages. Paper submitted in this track should be anonymized and can be submitted to the EasyChair conference management system by the same deadline as for the regular track. * Call for Lightning Talk Participants are invited to submit proposals for 5-minute lightning talks describing recently published results, work in progress, wild ideas, etc. Lightning talks are a new feature of SACMAT, introduced this year to partially replace the informal sharing of ideas at in-person meetings. Submit at https://easychair.org/my/conference?conf=sacmat21 by May 28, 2021 (the early registration deadline). Notification of acceptance on June 2, 2021. * Call for Posters SACMAT 2021 will include a poster session to promote discussion of ongoing projects among researchers in the field of access control and computer security. Posters can cover preliminary or exploratory work with interesting ideas, or research projects in early stages with promising results in all aspects of access control and computer security. Authors interested in displaying a poster must submit a poster abstract in the same format as for the regular track, but the length must not exceed three US letter pages, and the submission should not be anonymized. The title should start with "Poster:". Accepted poster abstracts will be included in the conference proceedings. Submissions for posters should be emailed to the poster chair, Dr. Diego Perino (Diego.perino at telefonica.com), by Apr 19, 2021, 5PM PDT. The subject line should include "SACMAT 2021 Poster:" followed by the poster title. * Call for Demos A demonstration proposal should clearly describe (1) the overall architecture of the system or technology to be demonstrated, and (2) one or more demonstration scenarios that describe how the audience, interacting with the demonstration system or the demonstrator, will gain an understanding of the underlying technology. Submissions will be evaluated based on the motivation of the work behind the use of the system or technology to be demonstrated and its novelty. The subject line should include "SACMAT 2021 Demo:" followed by the demo title. Demonstration proposals should be in the same format as for the regular track, but the length must not exceed four US letter pages, and the submission should not be anonymized. A two-page description of the demonstration will be included in the conference proceedings. Submissions should be emailed to the Demonstrations Chair, Dr. Diego Perino (Diego.perino at telefonica.com), by Apr 19, 2021, 5pm PDT. * Financial Conflict of Interest (COI) Disclosure: In the interests of transparency and to help readers form their own judgements of potential bias, ACM SACMAT requires authors and PC members to declare any competing financial and/or non-financial interests in relation to the work described. * Definition For the purposes of this policy, competing interests are defined as financial and non-financial interests that could directly undermine, or be perceived to undermine the objectivity, integrity and value of a publication, through a potential influence on the judgements and actions of authors with regard to objective data presentation, analysis and interpretation. Financial competing interests include any of the following: Funding: Research support (including salaries, equipment, supplies, and other expenses) by organizations that may gain or lose financially through this publication. A specific role for the funding provider in the conceptualization, design, data collection, analysis, decision to publish, or preparation of the manuscript, should be disclosed. Employment: Recent (while engaged in the research project), present or anticipated employment by any organization that may gain or lose financially through this publication. Personal financial interests: Ownership or contractual interest in stocks or shares of companies that may gain or lose financially through publication; consultation fees or other forms of remuneration (including reimbursements for attending symposia) from organizations that may gain or lose financially; patents or patent applications (awarded or pending) filed by the authors or their institutions whose value may be affected by publication. For patents and patent applications, disclosure of the following information is requested: patent applicant (whether author or institution), name of inventor(s), application number, status of application, specific aspect of manuscript covered in patent application. It is difficult to specify a threshold at which a financial interest become significant, but note that many US universities require faculty members to disclose interests exceeding $10,000 or 5% equity in a company. Any such figure is necessarily arbitrary, so we offer as one possible practical alternative guideline: "Any undeclared competing financial interests that could embarrass you were they to become publicly known after your work was published." We do not consider diversified mutual funds or investment trusts to constitute a competing financial interest. Also, for employees in non-executive or leadership positions, we do not consider financial interest related to stocks or shares in their company to constitute a competing financial interest, as long as they are publishing under their company affiliation. Non-financial competing interests: Non-financial competing interests can take different forms, including personal or professional relations with organizations and individuals. We would encourage authors and PC members to declare any unpaid roles or relationships that might have a bearing on the publication process. Examples of non-financial competing interests include (but are not limited to): ? Unpaid membership in a government or non-governmental organization ? Unpaid membership in an advocacy or lobbying organization ? Unpaid advisory position in a commercial organization ? Writing or consulting for an educational company ? Acting as an expert witness * Conference Code of Conduct and Etiquette ACM SACMAT will follow the ACM Policy Against Harassment at ACM Activities. Please familiarize yourself with the ACM Policy Against Harassment and guide to Reporting Unacceptable Behavior. * AUTHORS TAKE NOTE The official publication date is the date the proceedings are made available in the ACM Digital Library. This date may be up to two weeks prior to the first day of your conference. The official publication date affects the deadline for any patent filings related to published work. (For those rare conferences whose proceedings are published in the ACM Digital Library after the conference is over, the official publication date remains the first day of the conference.) -- Marinella Petrocchi Senior Researcher @Institute of Informatics and Telematics (IIT) National Research Council (CNR) Pisa (Italy) Mobile: +39 348 8260773 Skype: m_arinell_a Web: https://marinellapetrocchi.wixsite.com/mysite `Luck is a matter of geography' (Bandabardo') From ASIM.ROY at asu.edu Fri Oct 30 02:43:12 2020 From: ASIM.ROY at asu.edu (Asim Roy) Date: Fri, 30 Oct 2020 06:43:12 +0000 Subject: Connectionists: INTERNATIONAL NEURAL NETWORK SOCIETY (INNS) - FREE Inaugural Virtual Workshop on Explainable AI on November 6, 2020, Friday, 9 am to 1 pm EST - REGISTRATION IS OPEN NOW In-Reply-To: References: Message-ID: Just a reminder about this virtual workshop on Explainable AI next Friday, Nov 6. From: Connectionists On Behalf Of Asim Roy Sent: Wednesday, October 21, 2020 12:48 AM To: connectionists at mailman.srv.cs.cmu.edu; comp-neuro at neuroinformatics.be Subject: Connectionists: INTERNATIONAL NEURAL NETWORK SOCIETY (INNS) - FREE Inaugural Virtual Workshop on Explainable AI on November 6, 2020, Friday, 9 am to 1 pm EST - REGISTRATION IS OPEN NOW Dear Colleagues, We are pleased to announce that INNS (the International Neural Network Society) is launching a Virtual Technical Event series that will feature workshops, seminars, tutorials, discussions and so on. These technical events will occur throughout the year for a worldwide audience. We welcome proposals on challenging and controversial research topics and ones that provide new insights on biological learning. Through this series of virtual technical events, we would like to serve the growing need for advanced education in a variety of fields that are linked together such as AI, machine learning, neural networks, cognitive science, robotics and so on. Further details on proposal submission are available at https://www.inns.org/virtual-technical-events. We also welcome proposals from the industry and industry sponsorship of these events. FREE Inaugural Virtual Workshop on Explainable AI on November 6, 2020, Friday, 9 am to 1 pm EST This inaugural workshop focuses on Explainable AI (XAI), a topic that is highly important for us to widely deploy our AI/ML systems. We invited five prominent scholars to present their thoughts in this virtual workshop. Further details are provided below including where to register for the event. WORKSHOP SPEAKERS 1. Stephen Grossberg, Wang Professor of Cognitive and Neural Systems, Boston University, http://sites.bu.edu/steveg/ 2. Juergen Schmidhuber, Scientific Director of IDSIA, http://people.idsia.ch/~juergen/ 3. Jeff Krichmar, Professor of Cognitive Sciences, University of California, Irvine, http://www.socsci.uci.edu/~jkrichma 4. Vladimir Cherkassky, Professor of ECE, Univ. of Minnesota, https://ece.umn.edu/directory/cherkassky-vladimir/ 5. Lee Giles, Professor of Information Sciences, Pennsylvania State University, https://clgiles.ist.psu.edu/ MODERATORS: Asim Roy, Professor, Arizona State University (https://lifeboat.com/ex/bios.asim.roy) Daniel Levine, Professor, University of Texas at Arlington (https://www.uta.edu/psychology/people/daniel-levine.php) FORMAT: Each speaker - 35 minute presentation + 10 mins Q&A REGISTRATION - https://www.eventbrite.hk/e/explainable-ai-xai-virtual-workshop-registration-122938932657 With regards, Irwin King INNS President, FIEEE, FHKIE, DMACM, BoG APNNS & INNS Chair, Dept. of Computer Science & Engineering o +(852) 3943-8398 The Chinese University of Hong Kong f +(852) 2603-5024 Shatin, N.T., Hong Kong http://www.cse.cuhk.edu.hk/irwin.king Asim Roy VP, Industry Relations, INNS Chair, Committee for Virtual Technical Events, INNS Professor, Arizona State University https://lifeboat.com/ex/bios.asim.roy -------------- next part -------------- An HTML attachment was scrubbed... URL: From ahmethungari at gmail.com Thu Oct 29 15:57:35 2020 From: ahmethungari at gmail.com (Birkan Tunc) Date: Thu, 29 Oct 2020 15:57:35 -0400 Subject: Connectionists: Postdoctoral Fellow in Computational Behavior Analysis Message-ID: We are seeking postdoctoral fellow applicants with interest and experience in computational approaches and machine learning for use in quantitative measurement of human behavior. This research is conducted at the Center for Autism Research (CAR) in Children?s Hospital of Philadelphia (CHOP) and at University of Pennsylvania (UPenn), as a part of an NIH grant. The fellow will be part of a big multidisciplinary team that develops computer vision and machine learning tools to quantify children?s and adults? behavior in the context of a social interaction/conversation. Computational behavior analysis is an emerging and exciting domain within psychiatric research, harnessing the power of computer vision, machine learning, and mathematical modeling to better capture and quantify all observable human behavior. Developments in this domain have the potential to rapidly advance our understanding of human behavior, thereby also facilitating an extremely fruitful and rewarding career path for young computational scientists. CAR provides a unique environment for talented postdoctoral fellows to study the human mind and behavior, with collaborations between engineers, computational scientists, hardware developers, psychologists and psychiatrists. We offer expertise in computational analysis of human behavior, with specific expertise in developmental or psychiatric disorders. A key goal of the center is to develop tools to quantify human behavior and interactions from video and audio recordings, using state-of-the-art computer vision and machine learning techniques. The fellow will be responsible for: ? Developing computer vision techniques (e.g., face analysis, body movement analysis, gesture analysis) ? Validating developed tools using in-house clinical data, as well as publicly available datasets ? Performing pattern recognition on collected data (i.e., classification, regression, clustering, feature learning) The ideal applicant will have prior experience in statistical and quantitative methods, as well as an appetite to learn. Salary is very competitive and will be commensurate with background and experience. Please apply at https://form.jotform.com/203023641732141 . More information about our related projects can be found at http://www.birkantunc.com Job Requirements ? PhD in computer science, electronic engineering or a related field ? Research experience in computer vision and machine learning ? Proficiency in Python and/or MATLAB; C++ is a plus ? Strong self-motivation, strong problem-solving skills, and ability to generate novel ideas Desired ? Ability to make a 2 year commitment ? Publications in top computer vision and machine learning conferences and journals ? Research experience in quantifying human behavior (e.g., affective computing) -------------- next part -------------- An HTML attachment was scrubbed... URL: From dwang at cse.ohio-state.edu Thu Oct 29 13:14:09 2020 From: dwang at cse.ohio-state.edu (Wang, Deliang) Date: Thu, 29 Oct 2020 17:14:09 +0000 Subject: Connectionists: NEURAL NETWORKS, Nov. 2020 Message-ID: Neural Networks - Volume 131, November 2020 https:www.journals.elsevier.com/neural-networks Integral reinforcement learning based event-triggered control with input saturation Shan Xue, Biao Luo, Derong Liu Deep learning on image denoising: An overview Chunwei Tian, Lunke Fei, Wenxian Zheng, Yong Xu, ... Chia-Wen Lin Fast Deep Stacked Networks based on Extreme Learning Machine applied to regression problems Bruno Legora Souza da Silva, Fernando Kentaro Inaba, Evandro Ottoni Teatini Salles, Patrick Marques Ciarelli Sparse coding with a somato-dendritic rule Damien Drix, Verena V. Hafner, Michael Schmuker ASSAF: Advanced and Slim StegAnalysis Detection Framework for JPEG images based on deep convolutional denoising autoencoder and Siamese networks Assaf Cohen, Aviad Cohen, Nir Nissim Relation-Guided Representation Learning Zhao Kang, Xiao Lu, Jian Liang, Kun Bai, Zenglin Xu Improved object recognition using neural networks trained to mimic the brain's statistical properties Callie Federer, Haoyan Xu, Alona Fyshe, Joel Zylberberg Bifurcations in a fractional-order neural network with multiple leakage delays Chengdai Huang, Heng Liu, Xiangyun Shi, Xiaoping Chen, ... Jinde Cao DANTE: Deep alternations for training neural networks Vaibhav B. Sinha, Sneha Kudugunta, Adepu Ravi Sankar, Surya Teja Chavali, Vineeth N. Balasubramanian Hungarian layer: A novel interpretable neural layer for paraphrase identification Han Xiao MetalGAN: Multi-domain label-less image synthesis using cGANs and meta-learning Tomaso Fontanini, Eleonora Iotti, Luca Donati, Andrea Prati Twin minimax probability machine for pattern classification Liming Yang, Yakun Wen, Min Zhang, Xue Wang Compressing 3DCNNs based on tensor train decomposition Dingheng Wang, Guangshe Zhao, Guoqi Li, Lei Deng, Yang Wu SVM-Boosting based on Markov resampling: Theory and algorithm Hongwei Jiang, Bin Zou, Chen Xu, Jie Xu, Yuan Yan Tang Leveraging maximum entropy and correlation on latent factors for learning representations Zhicheng He, Jie Liu, Kai Dang, Fuzhen Zhuang, Yalou Huang Intermittent boundary stabilization of stochastic reaction-diffusion Cohen-Grossberg neural networks Xiao-Zhen Liu, Kai-Ning Wu, Weihai Zhang Two-hidden-layer feed-forward networks are universal approximators: A constructive approach Eduardo Paluzo-Hidalgo, Rocio Gonzalez-Diaz, Miguel A. Gutierez-Naranjo Global mu-synchronization of impulsive pantograph neural networks Xuechen Li, Nan Wang, Jungang Lou, Jianquan Lu Theory of deep convolutional neural networks II: Spherical analysis Zhiying Fang, Han Feng, Shuo Huang, Ding-Xuan Zhou Finite-time stabilization and energy consumption estimation for delayed neural networks with bounded activation function Chongyang Chen, Song Zhu, Min Wang, Chunyu Yang, Zhigang Zeng Synthesis of recurrent neural dynamics for monotone inclusion with application to Bayesian inference Peng Yi, ShiNung Ching Exponential synchronization of stochastic delayed memristive neural networks via a novel hybrid control Nijing Yang, Yongbin Yu, Shouming Zhong, Xiangxiang Wang, ... Jingye Cai Unsupervised multi-domain multimodal image-to-image translation with explicit domain-constrained disentanglement Weihao Xia, Yujiu Yang, Jing-Hao Xue Improved recurrent neural network-based manipulator control with remote center of motion constraints: Experimental results Hang Su, Yingbai Hu, Hamid Reza Karimi, Alois Knoll, ... Elena De Momi Memristor-based LSTM network with in situ training and its applications Xiaoyang Liu, Zhigang Zeng, Donald C. Wunsch II -------------- next part -------------- An HTML attachment was scrubbed... URL: From malini.vinita.samarasinghe at ini.ruhr-uni-bochum.de Fri Oct 30 04:35:03 2020 From: malini.vinita.samarasinghe at ini.ruhr-uni-bochum.de (Vinita Samarasinghe) Date: Fri, 30 Oct 2020 09:35:03 +0100 Subject: Connectionists: GEM 2021 - Call for papers - deadline extended Message-ID: <2f31a4fc-5444-0747-876b-bf1968390509@ini.ruhr-uni-bochum.de> The deadline to submit abstracts for the GEM 2021 workshop has been extended until 30.11.2020. Please visit https://easychair.org/cfp/gem2021 to submit your abstracts for both the main workshop and the PhD symposium. ** *GEM 2021 - Generative Episodic Memory: Interdisciplinary perspectives from psychology, neuroscience and philosophy* https://for2812.rub.de/gem2021 16-18 February 2021 The workshop will take place in virtual space and is free of charge. Abstracts for both the workshop and the PhD symposium, which will precede the workshop, are now being accepted via EasyChair https://easychair.org/cfp/gem2021 Keynote Speakers: Karl-Heinz B?uml - University Regensburg, Germany Dorthe Berntsen - Aarhus University, Denmark Amy Criss - Syracuse University, USA Dorothea Debus - University of Konstanz, Germany David Huber - University of Massachusetts, USA Sarah Robins - University of Kansas, USA Call for papers The DFG-funded research consortium ?FOR 2812 ? Constructing scenarios of the past? https://for2812.rub.de is proud to announce a call for papers for its first workshop on generative episodic memory. We invite submissions for talks and posters https://easychair.org/cfp/gem2021. Episodic memories are widely regarded as memories of personally experienced events. Early concepts about episodic memory were based on the storage model, according to which experiential content is preserved in memory and later retrieved. However, overwhelming empirical evidence suggests that the content of episodic memory is ? at least to a certain degree ? constructed in the act of remembering. Even though very few contemporary researchers would oppose this view of episodic memory as a generative process, it has not become the standard paradigm of empirical memory research. This is particularly true for studies of the neural correlates of episodic memory. Further hindering progress are large conceptual differences regarding episodic memory across different fields, such as neuroscience, philosophy, and psychology. This interdisciplinary workshop therefore aims to bring together researchers from all relevant fields to advance the state of the art in the research on generative episodic memory. FOR 2812 ?Constructing scenarios of the past: A new framework in episodic memory? consists of 9 researchers. Seven from the Ruhr University Bochum and two from the University of M?nster. The consortium adopts an interdisciplinary approach and investigates generative episodic memory from a conceptual, modeling, and experimental perspective using a common conceptual framework: scenario construction. Paper submission deadlines [GMT +1 (CET)]: Abstract submission - 30.11.2020 Notification of acceptance - 31.12.2020 Submission guidelines: Abstracts must be submitted in English and be no longer than 1 page. Submitted work must be original and unpublished. Abstracts must be submitted electronically through the GEM 2021 paper submission site on EasyChair https://easychair.org/cfp/gem2021. Authors will receive confirmation of receipt of their abstracts including an ID number after submission. You can edit your submission at any time before the deadline. We will consider only the final version. Program committee: Nikolai Axmacher - Faculty of Psychology - Ruhr University Bochum Sen Cheng - Institute for Neural Computation - Ruhr University Bochum Gerald Echterhoff - Faculty of Psychology - University of M?nster Albert Newen - Faculty of Philosophy - Ruhr University Bochum Ricarda Schubotz - Faculty of Psychology - University of M?nster Markus Werning - Faculty of Philosophy - Ruhr University Bochum Laurenz Wiskott - Institute for Neural Computation - Ruhr University Bochum Oliver Wolf - Faculty of Psychology - Ruhr University Bochum All questions regarding the workshop should be emailed to for2812 at rub.de Coordinator - Vinita Samarasinghe Secretary - Christiane Dahl Vinita Samarasinghe M.Sc., M.A. Science Manager Arbeitsgruppe Computational Neuroscience Institut f?r Neuroinformatik Ruhr-Universit?t Bochum, NB 3/26 Postfachnummer 110 Universit?tstr. 150 D-44801 Bochum Tel: +49 (0)234 32 27996 Email: samarasinghe at ini.rub.de -------------- next part -------------- An HTML attachment was scrubbed... URL: From d.mandic at imperial.ac.uk Fri Oct 30 04:49:36 2020 From: d.mandic at imperial.ac.uk (Danilo Mandic) Date: Fri, 30 Oct 2020 08:49:36 +0000 Subject: Connectionists: Reminder: Explainable AI, a free Inaugural Workshop by the International Neural Networks, Society, Friday, 6 November, 2020 Message-ID: Dear Colleagues, We are pleased to announce that INNS (the International Neural Network Society) is launching a Virtual Technical Event series that will feature workshops, seminars, tutorials, discussions and so on. These technical events will occur throughout the year for a worldwide audience. We welcome proposals on challenging and controversial research topics and ones that provide new insights on biological learning. Through this series of virtual technical events, we would like to serve the growing need for advanced education in a variety of fields that are linked together such as AI, machine learning, neural networks, cognitive science, robotics and so on. Further details on proposal submission are available at https://www.inns.org/virtual-technical-events . We also welcome proposals from the industry and industry sponsorship of these events. *_FREE Inaugural Virtual Workshop on Explainable AI on November 6, 2020, Friday, 9 am to 1 pm EST_* This inaugural workshop focuses on Explainable AI (XAI), a topic that is highly important for us to widely deploy our AI/ML systems. We invited five prominent scholars to present their thoughts in this virtual workshop. Further details are provided below including where to register for the event. *_WORKSHOP SPEAKERS_* 1. *Stephen Grossberg*, Wang Professor of Cognitive and Neural Systems, Boston University, http://sites.bu.edu/steveg/ 2. *Juergen Schmidhuber*, Scientific Director of IDSIA , http://people.idsia.ch/~juergen/ 3. *Jeff Krichmar*, Professor of Cognitive Sciences, University of California, Irvine, http://www.socsci.uci.edu/~jkrichma 4. *Vladimir Cherkassky*, Professor of ECE, Univ. of Minnesota, https://ece.umn.edu/directory/cherkassky-vladimir/ 5. *Lee Giles*, Professor of Information Sciences, Pennsylvania State University, https://clgiles.ist.psu.edu/ *_MODERATORS_*: *Asim Roy*, Professor, Arizona State University (https://lifeboat.com/ex/bios.asim.roy ) *Daniel Levine*, Professor, University of Texas at Arlington (https://www.uta.edu/psychology/people/daniel-levine.php ) *_FORMAT_*: Each speaker ? 35 minute presentation + 10 mins Q&A *_REGISTRATION_*- https://www.eventbrite.hk/e/explainable-ai-xai-virtual-workshop-registration-122938932657 With regards, Irwin King INNS President, FIEEE, FHKIE,?DMACM, BoG APNNS & INNS Chair, Dept. of Computer Science &?Engineering ?o +(852) 3943-8398 The Chinese University of Hong?Kong ? ? ? ? ? ? f +(852) 2603-5024 Shatin, N.T., Hong Kong http://www.cse.cuhk.edu.hk/irwin.king Asim Roy VP, Industry Relations, INNS Chair, Committee for Virtual Technical Events, INNS Professor, Arizona State University https://lifeboat.com/ex/bios.asim.roy Danilo Mandic VP, Public Relationships, INNS Imperial College London, UK www.commsp.ee.ic.ac.uk/~mandic -------------- next part -------------- An HTML attachment was scrubbed... URL: From blextar at gmail.com Fri Oct 30 08:36:48 2020 From: blextar at gmail.com (Luca Rossi) Date: Fri, 30 Oct 2020 20:36:48 +0800 Subject: Connectionists: CFP S+SSPR 2020 [Deadline extended 15 November 2020] Message-ID: Dear all, Please note that the submission deadline for S+SSPR 2020 has been extended to the *** 15th of November (firm deadline) ***. Due to the ongoing covid-19 pandemic this edition of S+SSPR will be ONLINE and FREE. Accepted papers will be published in Springer?s Lecture Notes in Computer Science (LNCS) series. The plain text CFP is listed below and for further information visit https://www.dais.unive.it/sspr2020/ Looking forward to your submissions, S+SSPR organising committee === CALL FOR PAPERS IAPR Joint International Workshops on 13th Statistical Techniques in Pattern Recognition (SPR) 18th Structural and Syntactic Pattern Recognition Workshop (SSPR) Time and place: 19-22 January 2021, Online event Paper submission deadline: 15 November 2020 (FIRM DEADLINE) S+SSPR 2020 is a joint event organised by Technical Committee 1 (Statistical Pattern Recognition Technique) and Technical Committee 2 (Structural and Syntactical Pattern Recognition) of the International Association of Pattern Recognition (IAPR). Following the trend of previous editions, S+SSPR 2020 will be held in close proximity to the International Conference on Pattern Recognition (ICPR). Authors are invited to submit papers addressing topics in statistical, structural or syntactic pattern recognition and their applications. Accepted papers will be published in Springer?s Lecture Notes in Computer Science (LNCS) series. For details see: http://www.dais.unive.it/sspr2020/ -- Luca Rossi Lecturer in Artificial Intelligence School of Electronic Engineering and Computer Science Queen Mary University of London https://blextar.github.io/luca-rossi/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From risto at cs.utexas.edu Fri Oct 30 23:38:09 2020 From: risto at cs.utexas.edu (Risto Miikkulainen) Date: Fri, 30 Oct 2020 20:38:09 -0700 Subject: Connectionists: Invitation: XPRIZE on COVID-19 predictive and prescriptive modeling Message-ID: <60AA7DC4-C0EF-4ECC-8D83-0A2F2D3329FA@cs.utexas.edu> We are thrilled to share that XPRIZE, in partnership with Cognizant, is launching the Pandemic Response Challenge on November 17. Because of the urgency of the topic, we are reaching out to potential participants now. The Pandemic Response Challenge will focus on the development of data-driven models to predict COVID-19 infection rates and prescribe Intervention Plans that regional governments, communities, and organizations can implement to contain the pandemic and reopen safely. We encourage teams to get started on their prediction and prescription models as soon as possible. Please share this information with others who may be interested in competing, but kindly refrain from sharing publicly until the official launch on November 17, 2020. For more information (i.e. competition guidelines, access to the GitHub repository and slack channel), visit https://xprize.org/pandemicresponse Additional Information: - Goal: Over a four month period, teams will develop predictive models that deliver localized predictions of COVID-19 transmission, and will create prescriptor models that represent a tradeoff between minimizing the number of COVID-19 cases while lessening stringency (economic and social impact) of the intervention plans. - Technical Skills Needed: This is a data-driven challenge. Teams need at least one member who is competent in Python, knows how to run a model, and can install a library in a Jupyter sandbox environment. Teams can use any methods, including machine learning, statistical, and epidemiological approaches. - Prize and Registration Details: $500,000 total, distributed to two winning teams ($250K each). You need to sign up at Xprize pandemic response site to access competition information, and fully register your team before December 8, 2020; registration is limited to the first 200 teams. -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: Prelaunch_Pandemic Response Challenge.pdf Type: application/pdf Size: 263672 bytes Desc: not available URL: -------------- next part -------------- An HTML attachment was scrubbed... URL: From marinella.petrocchi at iit.cnr.it Fri Oct 30 12:55:27 2020 From: marinella.petrocchi at iit.cnr.it (Marinella Petrocchi) Date: Fri, 30 Oct 2020 17:55:27 +0100 Subject: Connectionists: 1fst CfP ROMCIR 2021: Reducing Online Misinformation through Credible Information Retrieval Message-ID: <187f0540c178bcad58614796bb1b05c7@iit.cnr.it> Apologies for Cross Posting --- What: ROMCIR 2021: Reducing Online Misinformation through Credible Information Retrieval Where: Online Event (originally scheduled in Lucca, Italy) When: March 28-April 1, 2021 Colocated with: ECIR 2021 European Symposium on Information Retrieval https://www.ecir2021.eu/ Conference website: https://romcir2021.disco.unimib.it/ Submission link: https://easychair.org/conferences/?conf=romcir2021 Abstract registration deadline: December 22, 2020 Submission deadline: January 4, 2021 The central topic of the ROMCIR (Reducing Online Misinformation through Credible Information Retrieval) 2021 workshop, as part of the satellite events of the ECIR (European Conference on Information Retrieval) 2021 conference, concerns providing access to users to credible and/or verified information, to mitigate the information disorder phenomenon. By ?information disorder? we mean all forms of communication pollution, from misinformation made out of ignorance, to intentional sharing of false content. In this context, all those approaches that can serve to the assessment of the credibility of information circulating online and in social media, in particular, find their place. This topic is very broad, as it concerns different contents (e.g., Web pages, news, reviews, medical information, online accounts, etc.), different Web and social media platforms (e.g., microblogging platforms, social networking services, social question-answering systems, etc.), and different purposes (e.g., identifying false information, accessing information based on its credibility, retrieving credible information, etc.). The workshop solicits the sending of two types of contributions relevant to the workshop and suitable to generate discussion: - Original, unpublished contributions (pre-prints submitted to ArXiv are eligible) that will be included in an open-access post-proceedings volume of CEUR Workshop Proceedings (http://ceur-ws.org/), indexed by both Scopus and DBLP. - Already published or preliminary work that will not be included in the post-proceedings volume. All submissions will be undergo double-blind peer review by the programme committee. Submissions are to be done electronically through the EasyChair at: https://easychair.org/conferences/?conf=romcir2021 Instructions: Submissions must be at least: 10 pages long (regular papers) between 5 and 9 pages long (short papers) Co-Chairs: Fabio Saracco, IMT School For Advanced Studies, Lucca, Italy Marco Viviani, University of Milano-Bicocca, Milan, Italy -- Marinella Petrocchi Senior Researcher @Institute of Informatics and Telematics (IIT) National Research Council (CNR) Pisa (Italy) Mobile: +39 348 8260773 Skype: m_arinell_a Web: https://marinellapetrocchi.wixsite.com/mysite `Luck is a matter of geography' (Bandabardo') From ujfalussy.balazs at koki.hu Sat Oct 31 02:35:11 2020 From: ujfalussy.balazs at koki.hu (Balazs Ujfalussy) Date: Sat, 31 Oct 2020 07:35:11 +0100 Subject: Connectionists: postdoc and PhD positions in Budapest Message-ID: <1E7A4015-519E-46C5-9461-BD0C43D5C797@koki.hu> The newly established Laboratory of Biological Computation (https://biocomplab.wordpress.com/) is looking for highly motivated postdoctoral fellows and PhD students to investigate the role of hippocampus in model based planning and predictions. The focus of our laboratory is to understand how various biological phenomena (e.g., ion channels, dendritic spikes, synaptic clustering or theta sequences) contribute to the behaviorally relevant computations performed by the hippocampus. To achieve this we develop novel theories connecting hippocampal circuit dynamics to network function, combine biophysical modelling with in vivo-like input patterns and develop new tools for statistical analysis of hippocampal single neuron and populations activity patterns. The positions with a competitive salary are available from January 1st, 2021, initially for 1 year with the possibility of extension up to 5 years. We offer a stimulating environment in the Institute of Experimental Medicine, Budapest and active collaboration with experimental groups in the institute with the potential to get involved in the design of novel 2P imaging and virtual reality experiments in mice and/or in analysing the data. The ideal candidate has a strong background in quantitative disciplines (physics, math, computer science) and is competent in programming (e.g. python, matlab, R, C). It is an advantage to have an experience in biophysical modelling or analysis of in vivo population activity data (imaging or electrophysiology). Please send your CV, publication list, letter of motivation and contact information for at least two references to Balazs Ujfalussy (ujfalussy.balazs at koki.hu). The first evaluation round will begin on November 18th, 2020. The positions will remain open until filled. With best regards, Balazs Ujfalussy From maryam.tavakol.ut at gmail.com Sat Oct 31 09:16:14 2020 From: maryam.tavakol.ut at gmail.com (Maryam Tavakol) Date: Sat, 31 Oct 2020 14:16:14 +0100 Subject: Connectionists: PhD Position in Machine Learning (Reinforcement Learning) at TU Eindhoven Message-ID: Dear all, We are looking for a highly motivated and skilled PhD candidate to work in the area of Machine Learning. *Potential topics* include, but are not restricted to: * (Deep) Reinforcement Learning * (Contextual) Multi-Armed Bandits * Counterfactual Learning * Fairness-aware Learning * Fairness in Reinforcement Learning * Off-policy Reinforcement Learning * Modeling Bias in Machine Learning * Decision Making under Uncertainty * Auto ML * Explainable AI * Recommendation Systems The Uncertainty in Artificial Intelligence (UAI) group is a new and quickly growing group embedded in the Data and AI (DAI) cluster at the Eindhoven University of Technology. In the DAI cluster, we aim at developing foundations of AI for the present and the future. This includes the design of new AI methods, development of AI algorithms and tools with a view at expanding the reach of AI and its generalization abilities. In particular, we study foundational issues of robustness, safety, trust, reliability, tractability, scalability, interpretability and explainability of AI. For more information, please follow this link: https://jobs.tue.nl/nl/vacature/phd-position-in-machine-learning-864922.html The position is available as soon as possible. Best Regards, Maryam Tavakol http://maryamtavakol.com/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From evomusart at gmail.com Sat Oct 31 10:05:48 2020 From: evomusart at gmail.com (EvoMUSART 2021) Date: Sat, 31 Oct 2020 15:05:48 +0100 Subject: Connectionists: Call for Papers (extended submission deadline) - EvoMUSART 2021 - 10th International Conference on Artificial Intelligence in Music, Sound, Art and Design Message-ID: ------------------------------------------------ Call for papers for the 10th International Conference on Artificial Intelligence in Music, Sound, Art and Design (EvoMUSART) ? Please distribute ? Apologies for cross-posting ------------------------------------------------ The 10th International Conference on Artificial Intelligence in Music, Sound, Art and Design (EvoMUSART) will be held in Seville, Spain, on 7-9 April 2021, as part of the evo* event. EvoMUSART webpage: www.evostar.org/2021/evomusart *Extended submission deadline:* 19 November 2020 Conference: 7-9 April 2021 Special Issue on Genetic Programming and Evolvable Machines ? The journal ?Genetic Programming and Evolvable Machines" (Q2, IF: 1.78) will publish a Special Issue called ?Evolutionary computation in Art, music & Design?. The editors of this Special Issue will be Juan Romero and Penousal Machado. Some authors from EvoMUSART 2021 will be invited to submit a new paper to this Special Issue. The main goal of EvoMUSART is to bring together researchers who are using Artificial Intelligence techniques (e.g. Artificial Neural Network, Evolutionary Computation, Swarm, Cellular Automata, Alife) for artistic tasks such as Visual Art, Music, Architecture, Video, Digital Games, Poetry, or Design. The conference gives researchers in the field the opportunity to promote, present and discuss ongoing work in the area. Accepted papers will be published by Springer Verlag in the Lecture Notes in Computer Science series. We welcome submissions which use Artificial Intelligence techniques in the generation, analysis and interpretation of Art, Music, Design, Architecture and other artistic fields. Submissions must be at most 16 pages long, in Springer LNCS format. Each submission must be anonymised for a double-blind review process. The deadline for submission is 19 November 2020. Accepted papers will be presented orally or as posters at the event and included in the EvoMUSART proceedings published by Springer Verlag in a dedicated volume of the Lecture Notes in Computer Science series. Indicative topics include but are not limited to: * Systems that create drawings, images, animations, sculptures, poetry, text, designs, webpages, buildings, etc.; * Systems that create musical pieces, sounds, instruments, voices, sound effects, sound analysis, etc.; * Systems that create artefacts such as game content, architecture, furniture, based on aesthetic and/or functional criteria; * Systems that resort to artificial intelligence to perform the analysis of image, music, sound, sculpture, or some other types of artistic object; * Systems in which artificial intelligence is used to promote the creativity of a human user; * Theories or models of computational aesthetics; * Computational models of emotional response, surprise, novelty; * Representation techniques for images, videos, music, etc.; * Surveys of the current state-of-the-art in the area; * New ways of integrating the user in the process (e.g. improvisation, co-creation, participation). Submission link: https://easychair.org/my/conference?conf=evo2021 More information on the submission process and the topics of EvoMUSART can be found at: www.evostar.org/2021/evomusart Papers published in EvoMUSART can be found at: https://evomusart-index.dei.uc.pt We look forward to seeing you in Seville in 2021! The EvoMUSART 2021 organisers Juan Romero Tiago Martins Nereida Rodr?guez-Fernandez (publication chair) -------------- next part -------------- An HTML attachment was scrubbed... URL: From xiaochun.cheng at gmail.com Sat Oct 31 07:36:27 2020 From: xiaochun.cheng at gmail.com (Xiaochun Cheng) Date: Sat, 31 Oct 2020 11:36:27 -0000 Subject: Connectionists: Special Issue on Complex Industrial Intelligent Systems Message-ID: <003201d6af7a$1d6641c0$5832c540$@gmail.com> [ ** Apologies for cross postings **] Special Issue on Complex Industrial Intelligent Systems https://onlinelibrary.wiley.com/pb-assets/assets/1098111X/Complex%20Industri al%20Intelligent%20Systems%20SI-1599226479497.pdf International Journal of Intelligent Systems https://onlinelibrary.wiley.com/journal/1098111x -------------- next part -------------- An HTML attachment was scrubbed... URL: