Generative Adversarial Learning

GANs consist of two networks: generator and discriminator.

Autoencoder GANs <http://elarosca.net/slides/iccv_autoencoder_gans.pdf>_

It combines the reconstruction power of autoencoders with the sampling power of GANs.

Reference

[1]https://carpedm20.github.io/faces/