Out-of-DistributionDetectionwithAnAdaptive LikelihoodRatioonInformativeHierarchicalVAE

Neural Information Processing Systems 

Unsupervised out-of-distribution (OOD) detection is essential for the reliability ofmachine learning. Inthe literature, existing work has shown that higher-level semantics captured by hierarchical VAEs can be used to detect OOD instances.

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