Generative Adversarial Networks

Cycle-Consistent Adversarial Learning as Approximate Bayesian Inference
We formalize the problem of learning interdomain correspondences in the absence of paired data as Bayesian inference in a latent …
Louis Tiao, Edwin V. Bonilla, Fabio Ramos
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Cycle-Consistent Adversarial Learning as Approximate Bayesian Inference