arxiv
PublishedMay 27, 2026 at 4:00 AM
—neutral
Interpretability and Generalization Bounds for Learning Spatial Physics
Publisher summary· verbatim
arXiv:2506.15199v3 Announce Type: replace Abstract: While there are many applications of ML to scientific problems that look promising, visuals can be deceiving. Using numerical analysis techniques, we rigorously quantify the accuracy, convergence rates, and generalization bounds of certain ML model
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Originally published on arxiv ↗