Probabilistic skip connections attach a distance-aware probabilistic model to an intermediate layer of a pretrained classifier, selected by neural-collapse metrics, yielding deterministic UQ and OOD detection without retraining.
Stochastic gra- dient hamiltonian monte carlo
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Probabilistic Skip Connections for Deterministic Uncertainty Quantification in Deep Neural Networks
Probabilistic skip connections attach a distance-aware probabilistic model to an intermediate layer of a pretrained classifier, selected by neural-collapse metrics, yielding deterministic UQ and OOD detection without retraining.