This repository contains theory and pytorch code for building and training generative adverserial networks (GANs).
Models that have been implemented with corresponding theory:
- GAN [Paper] [Notebook]
- Conditional GAN [Paper] [Notebook]
- Deep Convolutional GAN [Paper] [Notebook] TODO
- Wasserstein GAN [Paper] [Notebook] TODO