WGAN-GP Presentation

Materials for my presentation on 17/07/2019 in Hong Kong Machine Learning Meetup. The topic is WGAN-GP (Wasserstein Generative Adversarial Network with Gradient Penalty)

Presentation Slide

You can view my presentation slide here

Gallery

Dependencies

1. tensorflow==1.5.0
2. numpy==1.14.3
3. pandas==0.23.4
4. sklearn==0.20.3
5. matplotlib==3.0.2
6. scipy==1.3.0
7. PIL==5.3.0
8. imageio==2.4.1

Acknowledgement

Part of the code is borrowed from the following

1. vanilla_gan
2. improved_wasserstein_gan
3. basic-gans

Reference

1. Improved Training of Wasserstein GANs
2. Wasserstein GAN
3. Generative Adversarial Nets