VOS: Learning What You Don’t Know by Virtual Outlier Synthesis
Out-of-distribution (OOD) detection has received much attention lately due to
its importance in the safe deployment of neural networks. One of the key
challenges is that models lack supervision signals from unknown data, and as a
result, can produce overconfident predictions on OOD data. Previous ap…
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