Author

Lukas Lao Beyer

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#machine learning Feb 2026

Flow Matching with Uncertainty Quantification and Guidance

Uncertainty-aware flow matching (UA-Flow) is proposed, a lightweight extension of flow matching that predicts the velocity field together with heteroscedastic uncertainty that tracks sample fidelity more consistently than element-wise baselines and that these signals also carry information about data-manifold support.

Juyeop Han, Lukas Lao Beyer, Sertac Karaman · arXiv.org · 8 citations