arXiv Machine Learning August 7, 2026 By Guillaume Couairon, Alexis Jacq, Yu-Han Wu, Renu Singh, Yana Hasson, Quentin Berthet, Romuald Elie

Kastor: An efficient fine-tuning strategy for generative emulation of PDE simulations

Read the original on arXiv Machine Learning →

arXiv:2608. 06107v1 Announce Type: new Abstract: Machine learning offers a promising avenue to accelerate physical simulations by replacing computationally expensive traditional Partial Differential Equation (PDE) solvers with fast, differentiable surrogate models.

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

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