Principled neuromorphic reservoir computing by Denis Kleyko, Christopher J. Kymn, Anthony Thomas, Bruno A. Olshausen, Friedrich T. Sommer, E. Paxon Frady

“…Abstract Reservoir computing advances the intriguing idea that a nonlinear recurrent neural circuit—the reservoir—can encode spatio-temporal input signals to enable efficient ways to perform tasks like classification or regression. …”
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Post-processing methods for delay embedding and feature scaling of reservoir computers by Jonnel Jaurigue, Joshua Robertson, Antonio Hurtado, Lina Jaurigue, Kathy Lüdge

“…Abstract Reservoir computing is a machine learning method that is well-suited for complex time series prediction tasks. …”
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Multifunctional Photonic Reservoir Computing Based on Semiconductor Laser With Optical Feedback by Liyue Zhang, Weijie Hong, Songsui Li, Wei Pan, Lianshan Yan, Bin Luo, Xihua Zou

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Similarity Learning and Generalization with Limited Data: A Reservoir Computing Approach by Sanjukta Krishnagopal, Yiannis Aloimonos, Michelle Girvan

“…We present two Reservoir Computing architectures, which loosely resemble neural dynamics, and show that a Reservoir Computer (RC) trained to identify relationships between image pairs drawn from a subset of training classes generalizes the learned relationships to substantially different classes unseen during training. …”
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Edge-of-Chaos and Chaotic Dynamics in Resistor-Inductor-Diode-Based Reservoir Computing by A. H. Abbas, Hend Abdel-Ghani, Ivan S. Maksymov

Subjects: “…Reservoir computing…”
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Efficient optimisation of physical reservoir computers using only a delayed input by Enrico Picco, Lina Jaurigue, Kathy Lüdge, Serge Massar

“…Abstract Reservoir computing is a machine learning algorithm for processing time dependent data which is well suited for experimental implementation. …”
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Normalized difference vegetation index prediction using reservoir computing and pretrained language models by John Olamofe, Ram Ray, Xishuang Dong, Lijun Qian

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Iono–Magnonic Reservoir Computing With Chaotic Spin Wave Interference Manipulated by Ion‐Gating by Wataru Namiki, Daiki Nishioka, Yuki Nomura, Takashi Tsuchiya, Kazuo Yamamoto, Kazuya Terabe

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Coherent all Optical Reservoir Computing for Equalization of Impairments in Coherent Fiber Optic Communication Systems by Shiva Kumar, Mahmoud M. T. Maghrabi, Mohamed H. Bakr, Toshihiko Hirooka, Masataka Nakazawa

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Cross-Brand Machine Learning of Coffee’s Temporal Liking from Temporal Dominance of Sensations Curves by Hiroharu Natsume, Shogo Okamoto

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End-to-End Stroke Imaging Analysis Using Effective Connectivity and Interpretable Artificial Intelligence by Wojciech Ciezobka, Joan Falco-Roget, Cemal Koba, Alessandro Crimi

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Reduced connection strength leads to enhancement of working memory capacity in cognitive training by Guiyang Lv, Tianyong Xu, Jinhang Li, Ping Zhu, Feiyan Chen, Dongping Yang, Guoguang He

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Gait Perception via Actual and Estimated Pneumatic Physical Reservoir Output by Junyi Shen, Tetsuro Miyazaki, Swaninda Ghosh, Toshihiro Kawase, Kenji Kawashima

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Simulating the impact of white matter connectivity on processing time scales using brain network models by Paul Triebkorn, Viktor Jirsa, Peter Ford Dominey

“…In this study we used reservoir computing with human derived connectivity to investigate the effect of the structural connectivity on time scales across brain regions during a narrative task paradigm. …”
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Dissipation Alters Modes of Information Encoding in Small Quantum Reservoirs near Criticality by Krai Cheamsawat, Thiparat Chotibut

“…Quantum reservoir computing (QRC) has emerged as a promising paradigm for harnessing near-term quantum devices to tackle temporal machine learning tasks. …”
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Integrated Photonic Neural Networks for Equalizing Optical Communication Signals: A Review by Luís C. B. Silva, Pablo R. N. Marciano, Maria J. Pontes, Maxwell E. Monteiro, Paulo S. B. André, Marcelo E. V. Segatto

“…From this review, it can be concluded that perceptron photonic neural networks perform slightly better in equalizing signals transmitted over greater distances than reservoir computing photonic neural networks, but with signals at lower data rates. …”
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