Uncertainty Principles of Encoding GANs

      Ruili Feng 1 Zhouchen Lin  2 3 Jiapeng Zhu 4 Deli Zhao 5 Jinren Zhou 5 Zheng-Jun Zha  1

             Abstract                  1. Introduction
                                   Generative Adversarial Networks (GANs) (Goodfellow
   The compelling synthesis results of Generative         et al., 2014) are powerful unsupervised models of estab-
   Adversarial Networks (GANs) demonstrate rich          lishing maps from simple latent distributions to  ...