Entropic GANs meet VAEs: A Statistical Approach to Compute Sample Likelihoods in GANs

Building on the success of deep learning, two modern approaches to learn a probability model from the data are Generative Adversarial Networks (GANs) and Variational AutoEncoders (VAEs). VAEs consider an explicit probability model for the data and compute a generative distribution by maximizing a variational lower-bound on the log-likelihood function... (read more)

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