Bridging GANs and Bayesian Neural Networks via Partial Stochasticity

Maurizio Filippone, Marius P. Linhard

Generative Adversarial Networks (GANs) are popular and successful generative models. Despite their success, optimization is notoriously challenging. In this work, we explain the su…