李宏毅 2018最新GAN课程 class 3 Theory behind GAN

 Too much limitation of Gaussian model. The images are too blurry. So any general model?

But if P_G(x;θ) is a neural network, it‘s impossible to calculate the likelihood. ????

 We don‘t know the formulation of PG and Pdata, so how to calculate the divergence???? ---->>> discriminator!!!

V(G,D) = maximum the output if data come from Pdata, and maximum the output of data from PG. --- >>> this process is identical to a binary classifier

李宏毅 2018最新GAN课程 class 3 Theory behind GAN

原文：https://www.cnblogs.com/ecoflex/p/9040918.html