GPT-PINN: Generative Pre-Trained Physics-Informed Neural Networks toward non-intrusive Meta-learning of parametric PDEs

Physics-Informed Neural Network (PINN) has proven itself a powerful tool to obtain the numerical solutions of nonlinear partial differential equations (PDEs) leveraging the expressivity of deep neural networks and the computing power of modern heterogeneous hardware. However, its training is still t...

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Vydáno v:	Finite elements in analysis and design Ročník 228; s. 104047
Hlavní autoři:	Chen, Yanlai, Koohy, Shawn
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier B.V 01.01.2024
Témata:	Meta-learning model order reduction Network of networks Non-intrusive learning Parametric PDEs Physics-Informed Neural Networks Physics-Informed Neural Networks Parametric PDEs Non-intrusive learning model order reduction Meta-learning Network of networks
ISSN:	0168-874X, 1872-6925
On-line přístup:	Získat plný text
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