Lost in the Folds: When Cross-Validation Is Not a Deep Ensemble for Uncertainty Estimation

arXiv:2605.18329v2 Announce Type: replace-cross Abstract: Ensemble disagreement is widely used as a proxy for epistemic uncertainty in medical image segmentation. In practice, many studies form ensembles via K-fold cross-validation (CV), yet refer to them as ``deep ensembles'' (DE). Because CV members are trained on different data subsets, their disagreement mixes seed-driven variability with data-exposure effects, which can change how uncertainty should be interpreted. We audit recent segmentation uncertainty studies and find that terminology--implementation mismatches are common. We then com

Source: arXiv cs.LG — read the full report at the original publisher.

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