arXiv Machine Learning August 14, 2026 By Zequn He, Celia Reina

Structure-preserving uncertainty quantification for GENERIC dynamics

Read the original on arXiv Machine Learning →

arXiv:2608. 12624v1 Announce Type: new Abstract: Structure-preserving machine learning embeds physical structure directly into model architectures, yet uncertainty quantification (UQ) for such hard-constrained models remains limited because standard UQ methods may violate the encoded admissibility conditions, require architectural modifications, or impose substantial computational costs.

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

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