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In recent years, the machine learning community has seen a continuous growing interest in research aimed at investigating dynamical aspects of both training procedures and machine learning models. Of particular interest among recurrent neural network
Externí odkaz:
http://arxiv.org/abs/2010.02860
Reservoir computing is a popular approach to design recurrent neural networks, due to its training simplicity and approximation performance. The recurrent part of these networks is not trained (e.g., via gradient descent), making them appealing for a
Externí odkaz:
http://arxiv.org/abs/2003.10585
Among the various architectures of Recurrent Neural Networks, Echo State Networks (ESNs) emerged due to their simplified and inexpensive training procedure. These networks are known to be sensitive to the setting of hyper-parameters, which critically
Externí odkaz:
http://arxiv.org/abs/1903.11691
Autor:
Verzelli, Pietro, Sacerdote, Laura
Simultaneous recordings from many neurons hide important information and the connections characterizing the network remain generally undiscovered despite the progresses of statistical and machine learning techniques. Discerning the presence of direct
Externí odkaz:
http://arxiv.org/abs/1903.08460
Akademický článek
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Echo State Networks (ESNs) are simplified recurrent neural network models composed of a reservoir and a linear, trainable readout layer. The reservoir is tunable by some hyper-parameters that control the network behaviour. ESNs are known to be effect
Externí odkaz:
http://arxiv.org/abs/1810.01742
Akademický článek
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Autor:
Verzelli, Pietro1 (AUTHOR), Nold, Andreas1,2 (AUTHOR), Sun, Chao3 (AUTHOR), Heilemann, Mike4 (AUTHOR), Schuman, Erin M.3 (AUTHOR), Tchumatchenko, Tatjana1,2,5 (AUTHOR) tatjana.tchumatchenko@uni-mainz.de
Publikováno v:
Scientific Reports. 12/29/2022, Vol. 12 Issue 1, p1-11. 11p.
Autor:
Squadrani, Lorenzo, Wert-Carvajal, Carlos, Bohmbach, Kirsten, Verzelli, Pietro, Müller-Komorowska, Daniel, Henneberger, Christian, Tchumatchenko, Tatjana
Bernstein Conference 2022 abstract. http://bernstein-conference.de
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::060761ad1154dfcd33da6753466d52ed
Dynamical systems have been used to describe a vast range of phenomena, including physical sciences, biology, neurosciences, and economics just to name a few. The development of a mathematical theory for dynamical systems allowed researchers to creat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______805::b736828fb2647a4a516b1c02c4836ca2
http://doc.rero.ch/record/333569/files/2022INF001.pdf
http://doc.rero.ch/record/333569/files/2022INF001.pdf