Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators

It is widely known that neural networks (NNs) are universal approximators of continuous functions. However, a less known but powerful result is that a NN with a single hidden layer can accurately approximate any nonlinear continuous operator. This universal approximation theorem of operators is sugg...

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Veröffentlicht in:Nature machine intelligence Jg. 3; H. 3; S. 218 - 229
Hauptverfasser: Lu, Lu, Jin, Pengzhan, Pang, Guofei, Zhang, Zhongqiang, Karniadakis, George Em
Format: Journal Article
Sprache:Englisch
Veröffentlicht: London Nature Publishing Group UK 01.03.2021
Nature Publishing Group
The Author(s), Springer Nature
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ISSN:2522-5839, 2522-5839
Online-Zugang:Volltext
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