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Reservoir computing is a machine learning method that is closely linked to dynamical systems theory. This connection is highlighted in a brief introduction ...
Reservoir computing consists of a recurrent neural network with a reservoir layer and a readout layer. By utilizing nonlinear spatial-temporal patterns against ...
Abstract. Reservoir computing (RC) studies the properties of large recurrent networks of artificial neurons, with either fixed or random con- nectivity.
Jun 8, 2023 · We present two architectures of spiking models, inspired from the theory of Reservoir Computing and Legendre Memory Units, for the Time Series Classification ( ...
Jun 1, 2022 · Reservoir computing (RC) is an ML framework leveraging a dynamic reservoir for a nonlinear transformation of sequential inputs and a readout for mapping the ...
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The aim of this Special Issue is to focus on new challenges for fully exploiting the potential of RC in machine learning applications and realizing extremely ...
Reservoir computing (RC) is a promising approach that could drastically reduce the cost of learning as the input gets projected into a higher dimensional space, ...
Topics of the special session: Novel Reservoir Computing models Deep Reservoir Computing Reservoir Computing for Big Data Physical, Neuromorphic and Photonic ...
Jun 2, 2020 · Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers.
Reservoir computing (RC) studies the properties of large recurrent networks of artificial neurons, with either fixed or random connectivity. Over the last years ...