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05/06/2023
Embedding bifurcations into pneumatic artificial muscle
Harnessing complex body dynamics has been a long-standing challenge in r...
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09/01/2022
Quantum-Classical Hybrid Information Processing via a Single Quantum System
Current technologies in quantum-based communications bring a new integra...
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07/16/2022
Quantum Noise-Induced Reservoir Computing
Quantum computing has been moving from a theoretical phase to practical ...
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07/06/2022
Composite FORCE learning of chaotic echo state networks for time-series prediction
Echo state network (ESN), a kind of recurrent neural networks, consists ...
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04/01/2022
Physical Deep Learning with Biologically Plausible Training Method
The ever-growing demand for further advances in artificial intelligence ...
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06/06/2021
Transient Chaos in BERT
Language is an outcome of our complex and dynamic human-interactions and...
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03/25/2021
Learning Temporal Quantum Tomography
Quantifying and verifying the control level in preparing a quantum state...
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09/01/2020
Universal Approximation Property of Quantum Feature Map
Encoding classical inputs into quantum states is considered as a quantum...
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06/16/2020
Higher-Order Quantum Reservoir Computing
Quantum reservoir computing (QRC) is an emerging paradigm for harnessing...
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05/03/2020
Physical reservoir computing – An introductory perspective
Understanding the fundamental relationships between physics and its info...
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02/13/2020
Designing spontaneous behavioral switching via chaotic itinerancy
Chaotic itinerancy is a frequently observed phenomenon in high-dimension...
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12/24/2019
Optimal short-term memory before the edge of chaos in driven random recurrent networks
The ability of discrete-time nonlinear recurrent neural networks to stor...
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06/11/2019
Dynamical Anatomy of NARMA10 Benchmark Task
The emulation task of a nonlinear autoregressive moving average model, i...
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12/13/2018
Information Processing Capability of Soft Continuum Arms
Soft Continuum arms, such as trunk and tentacle robots, can be considere...
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02/14/2018
Use of recurrent infomax to improve the memory capability of input-driven recurrent neural networks
The inherent transient dynamics of recurrent neural networks (RNNs) have...
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02/26/2016
