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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Bibliographic Details
Published in:Nature machine intelligence Vol. 3; no. 3; pp. 218 - 229
Main Authors: Lu, Lu, Jin, Pengzhan, Pang, Guofei, Zhang, Zhongqiang, Karniadakis, George Em
Format: Journal Article
Language:English
Published: London Nature Publishing Group UK 01.03.2021
Nature Publishing Group
The Author(s), Springer Nature
Subjects:
ISSN:2522-5839, 2522-5839
Online Access:Get full text
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