GANs have probably been one of the coolest ideas in computer science in the past few years. They've gone from generating fuzzy images of digits to photorealistic faces. I've been exploring GANs a lot, and I though I'd compile a list of all of the resources I found helpful.
If you've found any cool resources that you think belong here, be sure to submit a pull request!
NIPS workshop series on how to train GANs
Tips and Tricks for training GANs
A Brief Introduction to GANs (and how to code them)
Deep Diving into GANs: from theory to production
A Beginner's Guide to Generative Adversarial Networks (GANs)
KerasGAN - Python library with loads of implementations of GANs
DCGAN Tensorflow - Implementation of DCGAN in Tensorflow
CycleGAN - PyTorch implementation of CycleGAN
Wasserstein GAN - Code accompanying the Wasserstein GAN paper