Some Theoretical Insights into Wasserstein GANs

4 Jun 2020 Gérard Biau Maxime Sangnier Ugo Tanielian

Generative Adversarial Networks (GANs) have been successful in producing outstanding results in areas as diverse as image, video, and text generation. Building on these successes, a large number of empirical studies have validated the benefits of the cousin approach called Wasserstein GANs (WGANs), which brings stabilization in the training process... (read more)

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