arXiv Machine Learning June 19, 2026 By Christian Jimenez-Beltran, Aretha L. Teckentrup, Antonio Vergari, Konstantinos C. Zygalakis

Neural network surrogates with uncertainty quantification for inverse problems in partial differential equations

Read the original on arXiv Machine Learning →

arXiv:2606. 20417v1 Announce Type: new Abstract: Inverse problems for differential equations arise throughout science and engineering, where one seeks to infer unknown model parameters from noisy or incomplete observations.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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