arXiv Machine Learning August 17, 2026 By Jonas Weidner, Yeray Martin-Ruisanchez, Daniel Rueckert, Benedikt Wiestler, Julian Suk

Inpainting physics: self-supervised learning for context-driven fluid simulation

Read the original on arXiv Machine Learning →

arXiv:2605. 08832v3 Announce Type: replace Abstract: Neural surrogate models for computational fluid dynamics (CFD) are typically trained as forward operators that map explicit problem specifications, such as geometry and boundary conditions, to solution fields.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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