An end-to-end framework for uncertainty-aware validation of generative models
arXiv:2610.37398v1 Announce Type: new Abstract: Density estimation with generative models is a common task in the physical sciences, for example in background estimation in particle physics. Existing machine learning techniques, however, lack methods to quantify uncertainties that can be propagated…
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- 2026-10-28 04:00 · arXiv stat.ML
An end-to-end framework for uncertainty-aware validation of generative models