4.5k citations · 4.5k across the 2 of their papers we have counts for
2 papers
cs.LG2017★ 29 cited
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…
cs.LG2017★ 4.5k cited
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…