<html><head><meta http-equiv="Content-Type" content="text/html; charset=utf-8"></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;" class=""><div class=""><span style="font-weight: bold; font-family: Arial;" class="">We are excited to announce that the application for Oxford Machine Learning Summer School (OxML 2021) is now open.</span></div><div class=""><span style="font-family: Arial;" class="">Location: Virtual/Online</span></div><div class=""><span style="font-family: Arial;" class="">Dates: August 9-20, 2021 (two weeks)</span></div><div class=""><span style="font-family: Arial;" class="">Application deadline: April 30, 2021</span></div><div class=""><span style="font-family: Arial;" class="">Website: </span><a href="https://www.oxfordml.school/" rev="en_rl_none" style="font-family: Arial;" class="">www.oxfordml.school</a><span style="font-family: Arial;" class=""> </span></div><div class=""><br class=""></div><div class=""><span style="font-weight: bold; font-family: Arial;" class="">About OxML</span></div><ul class=""><li class=""><span style="font-family: Arial;" class="">OxML schools have a special focus on ML and </span><a href="https://sustainabledevelopment.un.org/" rev="en_rl_none" style="font-family: Arial;" class="">SDG</a><span style="font-family: Arial;" class="">; in addition to theoretical ML lectures, there will also be lectures on the applications of ML in SDG topic areas.</span></li><li class=""><span style="font-family: Arial;" class="">OxML 2021 is organised by AI for Global Goals, and in partnership with The University of Oxford’s Deep Medicine Program, and </span><a href="https://cifar.ca/" rev="en_rl_none" style="font-family: Arial;" class="">CIFAR</a><span style="font-family: Arial;" class="">.</span></li><li class=""><span style="font-family: Arial;" class="">You can find out more about last year’s event (OxML 2020) — including the previous speakers and agenda — </span><a href="https://www.oxfordml.school/oxml2020" rev="en_rl_none" style="font-family: Arial;" class="">here</a><span style="font-family: Arial;" class="">. Last year, we hosted participants from 70+ countries and connected them to our world-renown speakers in ML (and in ML's applications in medicine, or SDG3).</span></li><li class=""><span style="font-family: Arial;" class="">Due to the pandemic, and in order to prioritise our speakers’ and participants’ health and safety, OxML 2021 will take place August 9-20, 2021 and will be an online event.</span></li></ul><div class=""><br class=""></div><div class=""><br class=""></div><div class=""><span style="font-weight: bold; font-family: Arial;" class="">OxML 2021 will cover more topics in both theoretical and applied ML</span></div><div class=""><span style="font-family: Arial;" class="">The more theoretical lectures on modern ML/DL topics will cover:</span></div><ul class=""><li class=""><span style="font-family: Arial;" class="">Statistical/probabilistic ML (e.g., Bayesian ML, Gaussian processes, ...)</span></li><li class=""><span style="font-family: Arial;" class="">Representation learning, computer vision, and NLP (e.g., neural sequence models, knowledge graphs, ...)</span></li><li class=""><span style="font-family: Arial;" class="">Causal ML (e.g., probabilistic graphical models, causal deep learning, ...)</span></li><li class=""><span style="font-family: Arial;" class="">Graph neural networks and Geometric DL</span></li><li class=""><span style="font-family: Arial;" class="">Federated learning, transfer learning, knowledge distillation, and more</span></li></ul><div class=""><br class=""></div><div class=""><span style="font-family: Arial;" class="">The applied lectures (on ML and SDG) will cover:</span></div><ul class=""><li class=""><span style="font-family: Arial;" class="">ML and Medicine (e.g., imaging, genomics, electronic health records (EHR), drug discovery, …) [~2 days]</span></li><li class=""><span style="font-family: Arial;" class="">ML and Social Good (e.g., climate action, emerging risks, sustainable cities, …) [~1.5 days]</span></li></ul><div class=""><br class=""></div><div class=""><br class=""></div><div class=""><span style="font-weight: bold; font-family: Arial;" class="">Speakers</span></div><div class=""><span style="font-family: Arial;" class="">The school’s world-renowned speakers are from top ML research groups (e.g., Oxford, Cambridge, CIFAR, Amazon, DeepMind, Microsoft Research, and more). The speakers’ bios and more details on their talks will be announced in the coming weeks (you can follow the updates via the </span><a href="https://www.oxfordml.school/" style="font-family: Arial;" class="">school’s website</a><span style="font-family: Arial;" class=""> and </span><a href="https://twitter.com/GlobalGoalsAI" rev="en_rl_none" style="font-family: Arial;" class="">Twitter</a><span style="font-family: Arial;" class=""> handle). </span></div><div class=""><br class=""></div><div class=""><br class=""></div><div class=""><span style="font-weight: bold; font-family: Arial;" class="">Target audience </span></div><ul class=""><li class=""><span style="font-family: Arial;" class="">Everyone is welcome to apply to OxML 2021 regardless of their origin, nationality, and country of residence.</span></li><li class=""><span style="font-family: Arial;" class="">Our primary target audience are (1) PhD students with good technical background whose research topics are related to ML, plus (2) researchers and engineers in both academia and industry with similar/advanced levels of technical knowledge. </span></li><li class=""><span style="font-family: Arial;" class="">All applicants are subject to a selection process; we aim to select strongly motivated participants, who are interested in broadening their knowledge of the advanced topics in the field of ML/DL and their applications.</span></li></ul><div class=""><br class=""></div><div class=""><br class=""></div><div class=""><span style="font-weight: bold; font-family: Arial;" class="">Application </span></div><ul class=""><li class=""><div class=""><span style="font-family: Arial;" class="">The application deadline is April 30, 2021; those interested can apply through the<span style="color: rgb(51, 51, 51);" class=""> </span><a style="color: rgb(51, 51, 51);" href="https://docs.google.com/forms/d/e/1FAIpQLSfVriKTBkFLOYG_RFRcLruoUtN8Y0Dmaf-veP9rmJ55a2Bumg/viewform?usp=sf_link" class="">application page</a><span style="color: rgb(51, 51, 51);" class=""> or via the School's website. </span></span></div></li><li class=""><span style="font-family: Arial;" class="">The application portal may close earlier than the deadline if the number of applications exceeds our capacity to review (last year we had more than 10x more applicants than we planned to accept).</span></li><li class=""><span style="font-family: Arial;" class="">There is no application fee.</span></li><li class=""><span style="font-family: Arial;" class="">For the accepted applicants, there will be a registration fee (please refer to the application form or </span><a href="https://www.oxfordml.school/faq" rev="en_rl_none" style="font-family: Arial;" class="">FAQ</a><span style="font-family: Arial;" class=""> page for more details). </span></li><li class=""><span style="font-family: Arial;" class="">Participants will have access to all lectures, plus the event’s community portal (e.g., Q&A and chat environment for participants and speakers/TAs, ML programming workshops, recordings of the lectures [for a limited time], the unconference track, networking, and more). </span></li></ul><div class=""><br class=""></div><div class=""><br class=""></div><div class=""><span style="font-weight: bold; font-family: Arial;" class="">Contacting Us </span></div><div class=""><span style="font-family: Arial;" class="">For any queries, you can contact us using this email address: </span><a href="mailto:contact@oxfordml.school" rev="en_rl_none" style="font-family: Arial;" class="">contact@oxfordml.school</a></div><div class=""><span style="font-family: Arial;" class="">Of course, more information (and possible the answers to some of the questions) can be found on the FAQ section of the website. </span></div><div class=""><br class=""></div><div class=""><span style="font-family: Arial;" class="">Best,</span></div><div class=""><span style="font-family: Arial;" class="">—</span></div><div class=""><span style="font-family: Arial;" class="">Reza Khorshidi, D.Phil. (Oxon)</span></div><div class=""><span style="font-family: Arial;" class="">Deep Medicine Program, Oxford Martin School</span></div><div class=""></div></body></html>