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stat.ML2019
Rethinking Generative Mode Coverage: A Pointwise Guaranteed Approach
Peilin Zhong, Yuchen Mo, Chang Xiao +2
Many generative models have to combat . The conventional wisdom to this end is by reducing through training a statistical distance (such as -divergence)…
stat.ML2018
BourGAN: Generative Networks with Metric Embeddings
Chang Xiao, Peilin Zhong, Changxi Zheng
This paper addresses the mode collapse for generative adversarial networks (GANs). We view modes as a geometric structure of data distribution in a metric space. Under this geometr…