482 citations · 1.3k across the 38 of their papers we have counts for
3 papers · 1 filter
Empirical Analysis of Overfitting and Mode Drop in GAN Training
Yasin Yazici, Chuan-Sheng Foo, Stefan Winkler +2
We examine two key questions in GAN training, namely overfitting and mode drop, from an empirical perspective. We show that when stochasticity is removed from the training procedur…
Classify and Generate: Using Classification Latent Space Representations for Image Generations
Saisubramaniam Gopalakrishnan, Pranshu Ranjan Singh, Yasin Yazici +3
Utilization of classification latent space information for downstream reconstruction and generation is an intriguing and a relatively unexplored area. In general, discriminative re…
Scalable and Practical Natural Gradient for Large-Scale Deep Learning
Kazuki Osawa, Yohei Tsuji, Yuichiro Ueno +3
Large-scale distributed training of deep neural networks results in models with worse generalization performance as a result of the increase in the effective mini-batch size. Previ…