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arXiv · 2312.03496

Variational Formulations of the Strong Formulation -- Forward and Inverse Modeling using Isogeometric Analysis and Physics-Informed Networks

Kent-Andre Mardal·Jarle Sogn·Marius Zeinhofer
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Abstract

The recently introduced Physics-Informed Neural Networks (PINNs) have popularized least squares formulations of both forward and inverse problems involving partial differential equations (PDEs) in strong form. We employ both Isogeometric Analysis and Physics-Informed Networks.

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Kent-Andre Mardal, Jarle Sogn, Marius Zeinhofer. 2023-12-06. Variational Formulations of the Strong Formulation -- Forward and Inverse Modeling using Isogeometric Analysis and Physics-Informed Networks. https://arxiv.org/abs/2312.03496

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