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Fast Learning Rates for Physics-Informed Kernel Methods

This story is from 2026-09-17. It is preserved in the archive; the latest stories are on the live feed.

arXiv:2609.18901v1 Announce Type: new Abstract: In physics-informed machine learning, a target function $u^*$ is learned from noisy value observations $y_i=u^*(x_i)+ \varepsilon_i$, together with differential information, given either by noisy observations $d_j=(Du^*)(z_j)+\xi_j$ or by a known phys…

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  1. 2026-09-17 04:00 · arXiv stat.ML
    Fast Learning Rates for Physics-Informed Kernel Methods

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