Lipschitz Generative Adversarial Nets
International Conference on Machine Learning, pp. 7584-7593, 2019.
In this paper, we study the convergence of generative adversarial networks (GANs) from the perspective of the informativeness of the gradient of the optimal discriminative function. We show that GANs without restriction on the discriminative function space commonly suffer from the problem that the gradient produced by the discriminator is...More
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