420 citations · 1.5k across the 35 of their papers we have counts for
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Step-like dependence of memory function on pulse width in spintronics reservoir computing
Terufumi Yamaguchi, Nozomi Akashi, Kohei Nakajima +3
Physical reservoir computing is a type of recurrent neural network that applies the dynamical response from physical systems to information processing. However, the relation betwee…
Quantum reservoir computing: a reservoir approach toward quantum machine learning on near-term quantum devices
Keisuke Fujii, Kohei Nakajima
Quantum systems have an exponentially large degree of freedom in the number of particles and hence provide a rich dynamics that could not be simulated on conventional computers. Qu…
Universal Approximation Property of Quantum Machine Learning Models in Quantum-Enhanced Feature Spaces
Takahiro Goto, Quoc Hoan Tran, Kohei Nakajima
Encoding classical data into quantum states is considered a quantum feature map to map classical data into a quantum Hilbert space. This feature map provides opportunities to incor…
Periodic structure of memory function in spintronics reservoir with feedback current
Terufumi Yamaguchi, Nozomi Akashi, Sumito Tsunegi +3
The role of the feedback effect on physical reservoir computing is studied theoretically by solving the vortex-core dynamics in a nanostructured ferromagnet. Although the spin-tran…
Higher-Order Quantum Reservoir Computing
Quoc Hoan Tran, Kohei Nakajima
Quantum reservoir computing (QRC) is an emerging paradigm for harnessing the natural dynamics of quantum systems as computational resources that can be used for temporal machine le…
Physical reservoir computing -- An introductory perspective
Kohei Nakajima
Understanding the fundamental relationships between physics and its information-processing capability has been an active research topic for many years. Physical reservoir computing…
Designing spontaneous behavioral switching via chaotic itinerancy
Katsuma Inoue, Kohei Nakajima, Yasuo Kuniyoshi
Chaotic itinerancy is a frequently observed phenomenon in high-dimensional and nonlinear dynamical systems, and it is characterized by the random transitions among multiple quasi-a…
Computing with vortices: Bridging fluid dynamics and its information-processing capability
Ken Goto, Kohei Nakajima, Hirofumi Notsu
Herein, the Karman vortex system is considered to be a large recurrent neural network, and the computational capability is numerically evaluated by emulating nonlinear dynamical sy…