MahaVar augments the Mahalanobis OOD score with class-wise distance variance, which is theoretically higher for in-distribution samples under relaxed Neural Collapse geometry.
Out-of-distribution detection in medical image analysis: A survey,
2 Pith papers cite this work. Polarity classification is still indexing.
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Noise injection during training reduces the ID-OOD performance gap in COVID-19 CXR classification from 0.10-0.20 to 0.01-0.06.
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MahaVar: OOD Detection via Class-wise Mahalanobis Distance Variance under Neural Collapse
MahaVar augments the Mahalanobis OOD score with class-wise distance variance, which is theoretically higher for in-distribution samples under relaxed Neural Collapse geometry.
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Noise Injection: Improving Out-of-Distribution Generalization for Limited Size Datasets
Noise injection during training reduces the ID-OOD performance gap in COVID-19 CXR classification from 0.10-0.20 to 0.01-0.06.