Michael U. Gutmann
VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational Learning
Akash Srivastava, Lazar Valkov, Chris Russell, Michael U. Gutmann, Charles Sutton
Deep generative models provide powerful tools for distributions over complicated manifolds, such as those of natural images. But many of these methods, including generative adversarial networks (GANs), can be difficult to train, in part because they are prone to mode collapse, which means that they characterize only a few modes of the true distribution.
VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational Learning
Akash Srivastava, Lazar Valkov, Chris Russell, Michael U. Gutmann, Charles Sutton
Neural Information Processing Systems http://nips.cc/