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Fast Decision Boundary based Out-of-Distribution Detector
We investigate from the novel perspective of decision boundaries and propose to detect OOD using the feature distance to decision boundaries.
Computational Efficiency
Out of Distribution (OOD) Detection
Detecting Out-of-Distribution Through the Lens of Neural Collapse
Particularly, based on the recent observation, Neural Collapse, we further demonstrate that ID features tend to cluster in proximity to weight vectors.
