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Ariel Elnekave

2 accepted papers

2025

Do WGANs succeed because they minimize the Wasserstein Distance? Lessons from Discrete Generators

ICLR 2025poster

Since WGANs were first introduced, there has been considerable debate whether their success in generating realistic images can be attributed to minimizing the Wasserstein distance between the distribution of generated images and the training distribution. In this paper we present theoretical and ex…

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