2022
Density-driven Regularization for Out-of-distribution Detection
NeurIPS 2022accept
Detecting out-of-distribution (OOD) samples is essential for reliably deploying deep learning classifiers in open-world applications. However, existing detectors relying on discriminative probability suffer from the overconfident posterior estimate for OOD data. Other reported approaches either impo…