Physics-informed attention-based neural network for hyperbolic partial differential equations: application to the Buckley–Leverett problem

Physics-informed neural networks (PINNs) have enabled significant improvements in modelling physical processes described by partial differential equations (PDEs) and are in principle capable of modeling a large variety of differential equations. PINNs are based on simple architectures, and learn the...

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Detalles Bibliográficos
Autores principales: Rodriguez-Torrado, Ruben, Ruiz, Pablo, Cueto-Felgueroso, Luis, Green, Michael Cerny, Friesen, Tyler, Matringe, Sebastien, Togelius, Julian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9085858/
https://www.ncbi.nlm.nih.gov/pubmed/35534639
http://dx.doi.org/10.1038/s41598-022-11058-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9085858/
https://www.ncbi.nlm.nih.gov/pubmed/35534639
http://dx.doi.org/10.1038/s41598-022-11058-2

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