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Wasserstein Generative Adversarial Networks
proceedings.mlr.pressWasserstein 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-