25 citations · 37 across the 2 of their papers we have counts for
2 papers
cs.NE2018★ 12 cited
Lipizzaner: A System That Scales Robust Generative Adversarial Network Training
Tom Schmiedlechner, Ignavier Ng Zhi Yong, Abdullah Al-Dujaili +2
GANs are difficult to train due to convergence pathologies such as mode and discriminator collapse. We introduce Lipizzaner, an open source software system that allows machine lear…
cs.NE2018★ 25 cited
Towards Distributed Coevolutionary GANs
Abdullah Al-Dujaili, Tom Schmiedlechner, and Erik Hemberg +1
Generative Adversarial Networks (GANs) have become one of the dominant methods for deep generative modeling. Despite their demonstrated success on multiple vision tasks, GANs are d…