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

Research article (Finite Elements in Analysis and Design, 2023) · cited 48× · AI/ML
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GPT-PINN: Generative Pre-Trained Physics-Informed Neural Networks toward non-intrusive Meta-learning of parametric PDEs

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GPT-PINN: Generative Pre-Trained Physics-Informed Neural Networks toward non-intrusive Meta-learning of parametric PDEs is a scholarly article[1].

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  • GPT-PINN: Generative Pre-Trained Physics-Informed Neural Networks toward non-intrusive Meta-learning of parametric PDEs's instance of is recorded as scholarly article[2].

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  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). GPT-PINN: Generative Pre-Trained Physics-Informed Neural Networks toward non-intrusive Meta-learning of parametric PDEs. Retrieved May 24, 2026, from https://4ort.xyz/entity/gpt-pinn-generative-pre-trained-physics-informed-neural-networks-toward-non-intrusive-meta-learning-of-parametric-pdes
MLA “GPT-PINN: Generative Pre-Trained Physics-Informed Neural Networks toward non-intrusive Meta-learning of parametric PDEs.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/gpt-pinn-generative-pre-trained-physics-informed-neural-networks-toward-non-intrusive-meta-learning-of-parametric-pdes.
BibTeX @misc{4ortxyz_gpt-pinn-generative-pre-trained-physics-informed-neural-networks-toward-non-intrusive-meta-learning-of-parametric-pdes_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{GPT-PINN: Generative Pre-Trained Physics-Informed Neural Networks toward non-intrusive Meta-learning of parametric PDEs}}, year = {2026}, url = {https://4ort.xyz/entity/gpt-pinn-generative-pre-trained-physics-informed-neural-networks-toward-non-intrusive-meta-learning-of-parametric-pdes}, note = {Accessed: 2026-05-24}}
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