Results 11 to 20 of about 1,932,721 (285)
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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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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Attention-enhanced reservoir computing [PDF]
Physical Review AppliedPhotonic reservoir computing has been successfully utilized in time-series prediction as the need for hardware implementations has increased. Prediction of chaotic time series remains a significant challenge, an area where the conventional reservoir computing framework encounters limitations of prediction accuracy.
Felix Köster +3 more
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All-optical reservoir computing
Optics Express, 2012 Reservoir Computing is a novel computing paradigm which uses a nonlinear recurrent dynamical system to carry out information processing. Recent electronic and optoelectronic Reservoir Computers based on an architecture with a single nonlinear node and a delay loop have shown performance on standardized tasks comparable to state-of-the-art digital ...
Duport, Francois +4 more
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Passive frustrated nanomagnet reservoir computing [PDF]
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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RCbench: a unified framework for benchmarking reservoir computing systems
Neuromorphic Computing and EngineeringReservoir computing (RC) is a computational framework where a fixed dynamical reservoir projects an input into a higher-dimensional state that is then analyzed by a readout , which is trained to map the reservoir state into the desired output.
Davide Pilati +5 more
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Photorefractive reservoir computing
Optics LettersReservoir computing (RC) is a machine learning (ML) framework that has gained attention in recent years as the interest in alternative computing paradigms has grown. RC allows the utilization of physical systems to solve ML tasks. We demonstrate the use of the nonlinear photorefractive reservoir computer and perform tasks requiring both nonlinearity ...
Alveteg, Sebastian +3 more
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Optimization of Reservoir Waterflooding [PDF]
, 2014 Waterflooding is a common type of oil recovery techniques where water is pumped into the reservoir for increased productivity. Reservoir states change with time, as such, different injection and production settings will be required to lead the process
Grema, Alhaji Shehu
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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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Principled neuromorphic reservoir computing [PDF]
Nature CommunicationsReservoir 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. However, recently the idea of a
Denis Kleyko +5 more
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