Wasserstein Generative Adversarial Networks

Wasserstein Generative Adversarial Networks the other hand, training GANs is well known for being del-icate and unstable, for reasons theoretically investigated in (Arjovsky & Bottou,2017). In this paper, we direct our attention on the various ways to measure how close the model distribution and the real dis-

  Adversarial, Generative, Wasserstein, Wasserstein generative adversarial