Generative Adversarial Networks (GAN)

Deep models are usually trained in a two-phase paradigm, where data collection and network training are separated. This may not be efficient since data collection is blind to network training.

We present Optimal Transport GAN (OT-GAN), a variant of generative adversarial nets minimizing a new metric measuring the distance between the generator distribution and the data distribution