Self-adaptive physics-informed neural networks

Physics-Informed Neural Networks (PINNs) have emerged recently as a promising application of deep neural networks to the numerical solution of nonlinear partial differential equations (PDEs). However, it has been recognized that adaptive procedures are needed to force the neural network to fit accur...

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Vydané v:	Journal of computational physics Ročník 474; s. 111722
Hlavní autori:	McClenny, Levi D., Braga-Neto, Ulisses M.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Inc 01.02.2023
Predmet:	Numerical methods for PDE Physics-informed neural networks Scientific machine learning Numerical methods for PDE Physics-informed neural networks Scientific machine learning
ISSN:	0021-9991, 1090-2716
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