Memorization Precedes Generation: Learning Unsupervised GANs with Memory Networks

ICLR 2018 Youngjin KimMinjung KimGunhee Kim

We propose an approach to address two issues that commonly occur during training of unsupervised GANs. First, since GANs use only a continuous latent distribution to embed multiple classes or clusters of data, they often do not correctly handle the structural discontinuity between disparate classes in a latent space... (read more)

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