A generative model G can be seen as taking a random seed h (say, a sample from a multivariate Normal distribution) and converting it into an output string G(h) that “looks” like a real datapoint. Such models are popular in classical statistics but the simpler ones like Gaussian Mixtures or Dirichlet Processes seem insufficient for modeling complicated distributions on natural images or natural language.
http://www.offconvex.org/2017/03/15/GANs/
这句话写的还不错。
原文：http://www.cnblogs.com/jianyingzhou/p/7084741.html