4 papers
Ensemble Reservoir Computing for Physical Systems
Yuma Nakamura, Tomoyuki Kubota, Yusuke Imai +3
Physical computing exploits unconventional physical substrates to overcome limitations such as the high energy consumption inherent in digital computation. However, intrinsic noise…
Memory Determines Learning Direction: A Theory of Gradient-Based Optimization in State Space Models
JingChuan Guan, Tomoyuki Kubota, Yasuo Kuniyoshi +1
State space models (SSMs) have gained attention by showing potential to outperform Transformers. However, previous studies have not sufficiently addressed the mechanisms underlying…
Harnessing omnipresent oscillator networks as computational resource
Thomas Geert de Jong, Hirofumi Notsu, Kohei Nakajima
Nature is pervaded with oscillatory dynamics. In networks of coupled oscillators patterns can arise when the system synchronizes to an external input. Hence, these networks provide…
Reservoir Computing Generalized
Tomoyuki Kubota, Yusuke Imai, Sumito Tsunegi +1
A physical neural network (PNN) has both the strong potential to solve machine learning tasks and intrinsic physical properties, such as high-speed computation and energy efficienc…