The GAN is dead; long live the GAN! A Modern GAN Baseline

Yiwen Huang, Aaron Gokaslan, Volodymyr Kuleshov +1

There is a widely-spread claim that GANs are difficult to train, and GAN architectures in the literature are littered with empirical tricks. We provide evidence against this claim…