5 papers
Recycling computational processes of dynamic programming for combinatorial optimization problems: a reservoir computing approach
Sora Todaka, Akihiro Yamamoto, Nozomi Akashi
Reusing previously computed results is a long-standing principle for reducing computational cost, but such reuse has largely been confined to a single problem's computation. Sharin…
One-shot prediction of noise-induced bifurcations with reservoir computing
Nozomi Akashi, Takayuki Watanabe, Masato Hara +4
Dynamical systems can exhibit complex responses when noise is injected. In particular, dynamics can be qualitatively altered by dynamic noise, a phenomenon known as noise-induced b…
Incorporating Coupling Knowledge into Echo State Networks for Learning Spatiotemporally Chaotic Dynamics
Kuei-Jan Chu, Nozomi Akashi, Akihiro Yamamoto
Machine learning methods have shown promise in learning chaotic dynamical systems, enabling model-free short-term prediction and attractor reconstruction. However, when applied to…
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…
Exploiting Chaotic Dynamics as Deep Neural Networks
Shuhong Liu, Nozomi Akashi, Qingyao Huang +2
Chaos presents complex dynamics arising from nonlinearity and a sensitivity to initial states. These characteristics suggest a depth of expressivity that underscores their potentia…