Results 11 to 20 of about 19,366 (302)
Next generation reservoir computing [PDF]
Nature Communications, 2021 Reservoir computers are artificial neural networks that can be trained on small data sets, but require large random matrices and numerous metaparameters.
Daniel J. Gauthier +3 more
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Stochastic reservoir computers
Nature CommunicationsReservoir computing is a form of machine learning that utilizes nonlinear dynamical systems to perform complex tasks in a cost-effective manner when compared to typical neural networks.
Peter J. Ehlers +2 more
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Passive frustrated nanomagnet reservoir computing
Communications Physics, 2023 Reservoir computing (RC) has received recent interest because reservoir weights do not need to be trained, enabling extremely low-resource consumption implementations, which could have a transformative impact on edge computing and in-situ learning where ...
Alexander J. Edwards +12 more
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Symmetry-aware reservoir computing [PDF]
Physical Review E, 2021 10 pages, 7 ...
Wendson A. S. Barbosa +7 more
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, 2021 Editors: Kohei Nakajima, Ingo Fischer. This book is the first comprehensive book about reservoir computing (RC). RC is a powerful and broadly applicable computational framework based on recurrent neural networks. Its advantages lie in small training data set requirements, fast training, inherent memory and high flexibility for various hardware ...
Nakajima, Kohei, Fischer, Ingo
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Calibrated reservoir computers [PDF]
Chaos: An Interdisciplinary Journal of Nonlinear Science, 2020 We observe the presence of infinitely fine-scaled alternations within the performance landscape of reservoir computers aimed for chaotic data forecasting. We investigate the emergence of the observed structures by means of variations of the transversal stability of the synchronization manifold relating the observational and internal dynamical states ...
Y. A. Mabrouk, C. Räth
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Reservoir computing with swarms [PDF]
Chaos: An Interdisciplinary Journal of Nonlinear Science, 2021 We study swarms as dynamical systems for reservoir computing (RC). By example of a modified Reynolds boids model, the specific symmetries and dynamical properties of a swarm are explored with respect to a nonlinear time-series prediction task. Specifically, we seek to extract meaningful information about a predator-like driving signal from the swarm’s ...
Thomas Lymburn +3 more
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Reservoir computing with noise
Chaos: An Interdisciplinary Journal of Nonlinear Science, 2023 This paper investigates in detail the effects of measurement noise on the performance of reservoir computing. We focus on an application in which reservoir computers are used to learn the relationship between different state variables of a chaotic system. We recognize that noise can affect the training and testing phases differently.
Chad Nathe +5 more
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Optoelectronic Reservoir Computing [PDF]
Scientific Reports, 2012 Reservoir computing is a recently introduced, highly efficient bio-inspired approach for processing time dependent data. The basic scheme of reservoir computing consists of a non linear recurrent dynamical system coupled to a single input layer and a single output layer. Within these constraints many implementations are possible. Here we report an opto-
Paquot, Yvan +6 more
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Multifunctionality in a reservoir computer [PDF]
Chaos: An Interdisciplinary Journal of Nonlinear Science, 2021 Multifunctionality is a well observed phenomenological feature of biological neural networks and considered to be of fundamental importance to the survival of certain species over time. These multifunctional neural networks are capable of performing more than one task without changing any network connections.
Andrew Flynn +2 more
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