Parameter misspecification in physics-informed neural networks: A closed-form audit and its limits
arXiv:2610.23948v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) are trained to minimize the residual of a prescribed equation, so a low training loss does not indicate whether a coefficient in that equation was specified incorrectly. This study evaluates what can be inferre…
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- 2026-10-20 04:00 · arXiv cs.LG
Parameter misspecification in physics-informed neural networks: A closed-form audit and its limits