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Enforcing Dirichlet boundary conditions in physics-informed neural networks and variational physics-informed neural networks
In this paper, we present and compare four methods to enforce Dirichlet boundary conditions in Physics-Informed Neural Networks (PINNs) and Variational Physics-Informed Neural Networks (VPINNs). Such conditions are usually imposed by adding penalization terms in the loss function and properly choosi...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Elsevier
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10432987/ https://www.ncbi.nlm.nih.gov/pubmed/37600384 http://dx.doi.org/10.1016/j.heliyon.2023.e18820 |