PDE-constrained inverse problems at the $\sqrt{n}$ rate via debiased physics-informed neural networks
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arXiv:2609.12301v1 Announce Type: cross Abstract: We study the problem of estimating unknown parameters in PDE-constrained inverse problems from noisy observations, where the PDE solution is approximated using Physics-Informed Neural Networks (PINNs). While PINNs have demonstrated remarkable empiri…
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- 2026-09-14 04:00 · arXiv stat.ML
PDE-constrained inverse problems at the $\sqrt{n}$ rate via debiased physics-informed neural networks