began topic

Resources and Implementations of Generative Adversarial Nets which are focusing on how to stabilize training process and generate high quality images: DCGAN, WGAN, EBGAN, BEGAN, etc.

yfeng95

ProGAN with Standard, WGAN, WGAN-GP, LSGAN, BEGAN, DRAGAN, Conditional GAN, InfoGAN, and Auxiliary Classifier GAN training methods

RahulBhalley

PyTorch implemented generative models for CelebA dataset: DCGAN, LSGAN, WGAN, WGANGP, InfoGAN, BEGAN, VAE, VAEGAN

msurtsukov

Playing with MNIST. Machine Learning. Generative Models.

bchao1

Pytorch implementations of GANs

YeonwooSung