884 citations · 1.3k across the 18 of their papers we have counts for
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cs.LG2024★ 1 cited
Noise-Aware Training of Neuromorphic Dynamic Device Networks
Luca Manneschi, Ian T. Vidamour, Kilian D. Stenning +13
Physical computing has the potential to enable widespread embodied intelligence by leveraging the intrinsic dynamics of complex systems for efficient sensing, processing, and inter…
cs.LG2021★ 42 cited
Exploiting Multiple Timescales in Hierarchical Echo State Networks
Luca Manneschi, Matthew O. A. Ellis, Guido Gigante +3
Echo state networks (ESNs) are a powerful form of reservoir computing that only require training of linear output weights whilst the internal reservoir is formed of fixed randomly…