most citedImproving Out-of-Distribution Detection via Epistemic Uncertainty Adversarial Training

7 citations · 10 across the 3 of their papers we have counts for

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cs.LG2025

Multi-layer Radial Basis Function Networks for Out-of-distribution Detection

Amol Khanna, Chenyi Ling, Derek Everett +2

Existing methods for out-of-distribution (OOD) detection use various techniques to produce a score, separate from classification, that determines how ``OOD'' an input is. Our insig…

cs.LG2022★ 7 cited

Improving Out-of-Distribution Detection via Epistemic Uncertainty Adversarial Training

Derek Everett, Andre T. Nguyen, Luke E. Richards +1

The quantification of uncertainty is important for the adoption of machine learning, especially to reject out-of-distribution (OOD) data back to human experts for review. Yet progr…