Author

Simone Brugiapaglia

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Preprint Sep 2026

Into the danger zone: stable extrapolation in high-dimensional function and operator learning

This work identifies classes of holomorphic functions and operators for which the OOD generalization error converges at algebraic rates even in the presence of large distribution shifts, leading to what is termed a `blessing of high dimensionality'.

Ben Adcock, Simone Brugiapaglia, Xue-Meng Wang · 0 citations

#machine learning Preprint Sep 2026

Into the danger zone: stable extrapolation in high-dimensional function and operator learning

Out-of-distribution (OOD) generalization is a central challenge in scientific machine learning. We study regression problems in which the test distribution differs from the training distribution and ask: under what assumptions on the target function or operator is stable extrapolation possible, and how far beyond the t...

Ben Adcock, Simone Brugiapaglia, Xue-Meng Wang · 0 citations