"What do we learn? Debunking the Myth of Unsupervised Outlier Detection. (arXiv:2206.03698v2 [cs.CV] UPDATED)" — An investigation into what Auto-Encoders (AE) actually learn when they are posed to solve two different tasks and challenging the assumption that AEs are likely to be even better at reconstructing some types of Out-of-Distribution (OoD) samples.

Paper: http://arxiv.org/abs/2206.03698

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Unsupervised outlier detection …