7 citations · 7 across the 7 of their papers we have counts for
8 papers
Programming Spintronic Reservoir Computing
Yuichiro Terasaki, Yusuke Imai, Jason Z. Kim +1
We present a programming framework for a spintronic reservoir computer (RC) that maps prescribed input-output relationships directly onto the readout layer, bypassing conventional…
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…
Gradient-based optimization of spintronic devices
Yusuke Imai, Shuhong Liu, Nozomi Akashi +1
The optimization of physical parameters serves various purposes, such as system identification and efficiency in developing devices. Spin-torque oscillators have been applied to ne…
How noise affects memory in linear recurrent networks
JingChuan Guan, Tomoyuki Kubota, Yasuo Kuniyoshi +1
The effects of noise on memory in a linear recurrent network are theoretically investigated. Memory is characterized by its ability to store previous inputs in its instantaneous st…
Quantum reservoir computing with repeated measurements on superconducting devices
Toshiki Yasuda, Yudai Suzuki, Tomoyuki Kubota +8
Reservoir computing is a machine learning framework that uses artificial or physical dissipative dynamics to predict time-series data using nonlinearity and memory properties of dy…