2020
Likelihood Regret: An Out-of-Distribution Detection Score For Variational Auto-encoder
NeurIPS 2020poster
Deep probabilistic generative models enable modeling the likelihoods of very high dimensional data. An important application of generative modeling should be the ability to detect out-of-distribution (OOD) samples by setting a threshold on the likelihood. However, a recent study shows that probabili…