Tensorizing Generative Adversarial Nets

30 Oct 2017Xingwei CaoXuyang ZhaoQibin Zhao

Generative Adversarial Network (GAN) and its variants exhibit state-of-the-art performance in the class of generative models. To capture higher-dimensional distributions, the common learning procedure requires high computational complexity and a large number of parameters... (read more)

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