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Towards Generalized Implementation of Wasserstein Distance in GANs
[article]
2021
arXiv
pre-print
Wasserstein GANs (WGANs), built upon the Kantorovich-Rubinstein (KR) duality of Wasserstein distance, is one of the most theoretically sound GAN models. However, in practice it does not always outperform other variants of GANs. This is mostly due to the imperfect implementation of the Lipschitz condition required by the KR duality. Extensive work has been done in the community with different implementations of the Lipschitz constraint, which, however, is still hard to satisfy the restriction
arXiv:2012.03420v2
fatcat:akewv6hz3jew7lqtnd6sdcvghi