Connectionists: [CfP] 3rd International Workshop on Reservoir Computing (RC 2025) @ ICANN 2025 (deadline extension)

[Alessio Micheli]

Sorry for multiple and cross postings.

3<https://sites.google.com/view/reservoircomputing2025/home>rd<https://sites.google.com/view/reservoircomputing2025/home> International Workshop on Reservoir Computing @ ICANN 2025<https://sites.google.com/view/reservoircomputing2025/home>

Reservoir Computing (RC) denotes a class of recurrent neural models whose dynamics are left unadapted after initialization. The approach is appealing for several reasons, such as fast training, a natural propensity to edge computing and strong theoretical foundations with implications for the basic properties of recurrent neural networks in general.

After the success of the last year's edition, the 3rd International Workshop on Reservoir Computing (RC 2025) intends to once again bring back together researchers to update the discussion on the state-of-the-art and the cutting-edge challenges in the field of RC, in all its declinations.
Accepted contributions will be published as part of the ICANN 2025 proceedings in the Springer Lecture Notes in Computer Science<https://www.springer.com/gp/computer-science/lncs> (LNCS) series, indexed as a peer-reviewed publication in the Web of Science.
Follow the instructions to submit your contribution: LINK<https://sites.google.com/view/reservoircomputing2025/submission>.
Important dates
Deadline for full paper and extended abstract submission: 1 May 2025 15 May 2025 (final extension)
Notification of acceptance: 1 June 2025 15 June 2025
Camera-ready upload: 15 June 2025 25 June 2025
Conference dates: 9-12 September 2025
Topics
Topics of interest to this workshop include, but are not limited to:

  *   Echo State Networks, Liquid State Machines

  *   Hybrids of fully-trained and RC models

  *   Deep Reservoir Computing

  *   Reservoir Computing for structured data (trees, graphs, networks, …)

  *   Ensemble learning and Reservoir Computing

  *   Trustworthy AI concepts for Reservoir Computing

  *   Reservoir dimensionality reduction, efficient reservoir hyper-parameter search and learning

  *   Reservoir Computing in Neuroscience

  *   Theoretical analysis of Reservoir Computing

  *   Statistical Learning Theory of Reservoir Computing networks

  *   Reservoir Computing for AI applications (e.g., vision, natural language processing, health, bioinformatics, etc.)

Submission instructions
Submit your contribution using the instructions provided at https://e-nns.org/icann2025/submission on the conference management system. Select the “Workshop: Reservoir Computing” track on Microsoft CMT<https://cmt3.research.microsoft.com/ICANN2025>.
We follow a double-blind review process.
Call for reviewers
Please volunteer as a reviewer to help us ensure the quality of the papers presented at this workshop. Apply here<https://forms.gle/WGFLRE65R3uWjEKG6>.

Organizers

Alessio Micheli, University of Pisa, Italy

Gouhei Tanaka, Nagoya Institute of Technology, Japan

Domenico Tortorella, University of Pisa, Italy

Benjamin Paaßen, Bielefeld University, Germany

Claudio Gallicchio, University of Pisa, Italy

Xavier Hinaut, INRIA, France

Andrea Ceni, University of Pisa, Italy
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