Reservoir Computing (RC) denotes a class of recurrent neural models whose dynamics are left unadapted after initialization. The approach is appealing for several reasons, among which are extreme training efficiency, neuromorphic hardware implementations, and a natural propensity to edge computing.
In the wake of the recent success of the past edition at ICANN 2025, the 4th International Workshop on Reservoir Computing (RC 2026) intends to once more bring together researchers to discuss the state-of-the-art and open challenges in the field of RC, in all its declinations. These include, among others, new models of Echo State Networks and Liquid State Machines, non-conventional hardware (e.g., photonic) implementations of RC systems, applications to problems of AI size with human-level performance, emerging paradigms (e.g., conceptors), RC for structured data, deep RC, hybrid RC/fully trained RNN models, and many more. The workshop provides an open forum for researchers to meet and present recent contributions and ideas in a fervid and highly interdisciplinary environment. Industrial contributions are welcome.
Workshop Organizers
- Domenico Tortorella
- Benjamin Paassen
- Andrea Ceni
- Gouhei Tanaka
- Anna Bison
- Claudio Gallicchio