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05/19/2021
Do We Really Need to Learn Representations from In-domain Data for Outlier Detection?
Unsupervised outlier detection, which predicts if a test sample is an ou...
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02/23/2021
EBMs Trained with Maximum Likelihood are Generator Models Trained with a Self-adverserial Loss
Maximum likelihood estimation is widely used in training Energy-based mo...
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06/15/2020
Exponential Tilting of Generative Models: Improving Sample Quality by Training and Sampling from Latent Energy
In this paper, we present a general method that can improve the sample q...
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03/06/2020
Likelihood Regret: An Out-of-Distribution Detection Score For Variational Auto-encoder
Deep probabilistic generative models enable modeling the likelihoods of ...
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11/05/2019
A Method to Model Conditional Distributions with Normalizing Flows
In this work, we investigate the use of normalizing flows to model condi...
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05/24/2019