17 citations · 46 across the 6 of their papers we have counts for
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stat.ML2020★ 4 cited
Approximating Lipschitz continuous functions with GroupSort neural networks
Ugo Tanielian, Maxime Sangnier, Gerard Biau
Recent advances in adversarial attacks and Wasserstein GANs have advocated for use of neural networks with restricted Lipschitz constants. Motivated by these observations, we study…
stat.ML2018★ 9 cited
Some Theoretical Properties of GANs
G. Biau, B. Cadre, M. Sangnier +1
Generative Adversarial Networks (GANs) are a class of generative algorithms that have been shown to produce state-of-the art samples, especially in the domain of image creation. Th…