Karol Kurach, Mario Lucic, Xiaohua Zhai, Marcin Michalski, Sylvain Gelly
TL;DR本文从实用角度出发，分析评估生成对抗网络的常见错误和可重现性问题，并提供预训练模型。
Abstract
generative adversarial networks (GANs) are a class of deep generative models which aim to learn a target distribution in an unsupervised fashion. While they were successfully applied to many problems, training a