Adversarial Networks and Autoencoders: The Primal-Dual Relationship and Generalization Bounds
arXiv: Machine Learning, 2019.
Since the introduction of Generative Adversarial Networks (GANs) and Variational Autoencoders (VAE), the literature on generative modelling has witnessed an overwhelming resurgence. The impressive, yet elusive empirical performance of GANs has lead to the rise of many GAN-VAE hybrids, with the hopes of GAN level performance and additional...More
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