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Differentiable Physics-Neural Models enable Learning of Non-Markovian Closures for Accelerated Coarse-Grained Physics Simulations

Fuente: arXiv

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Detalles Bibliográficos
Autores principales:	Xue, Tingkai, Ooi, Chin Chun, Ge, Zhengwei, Leong, Fong Yew, Li, Hongying, Kang, Chang Wei
Formato:	Preprint
Publicado:	2025
Materias:	Computational Physics Machine Learning Fluid Dynamics
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

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