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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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Dettagli Bibliografici
Autori principali:	Xue, Tingkai, Ooi, Chin Chun, Ge, Zhengwei, Leong, Fong Yew, Li, Hongying, Kang, Chang Wei
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Computational Physics Machine Learning Fluid Dynamics
Accesso online:	Acceder al recurso
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