4.5k citations · 5.1k across the 4 of their papers we have counts for
4 papers
Coulomb GANs: Provably Optimal Nash Equilibria via Potential Fields
Thomas Unterthiner, Bernhard Nessler, Calvin Seward +4
Generative adversarial networks (GANs) evolved into one of the most successful unsupervised techniques for generating realistic images. Even though it has recently been shown that…
GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner +2
Generative Adversarial Networks (GANs) excel at creating realistic images with complex models for which maximum likelihood is infeasible. However, the convergence of GAN training h…
Self-Normalizing Neural Networks
Günter Klambauer, Thomas Unterthiner, Andreas Mayr +1
Deep Learning has revolutionized vision via convolutional neural networks (CNNs) and natural language processing via recurrent neural networks (RNNs). However, success stories of D…
Toxicity Prediction using Deep Learning
Thomas Unterthiner, Andreas Mayr, Günter Klambauer +1
Everyday we are exposed to various chemicals via food additives, cleaning and cosmetic products and medicines -- and some of them might be toxic. However testing the toxicity of al…