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Recipes for when physics fails: recovering robust learning of physics informed neural networks
Physics-informed neural networks (PINNs) have been shown to be effective in solving partial differential equations by capturing the physics induced constraints as a part of the training loss function. This paper shows that a PINN can be sensitive to errors in training data and overfit itself in dyna...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
IOP Publishing
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10481851/ https://www.ncbi.nlm.nih.gov/pubmed/37680302 http://dx.doi.org/10.1088/2632-2153/acb416 |