Skip to content

Latest commit

 

History

History
28 lines (23 loc) · 1.21 KB

README.md

File metadata and controls

28 lines (23 loc) · 1.21 KB

Generative Models

Collection of generative models, e.g. GAN, VAE in Tensorflow, Keras, and Pytorch.

Note: generated samples will be stored in GAN/{gan_model}/out or VAE/{vae_model}/out directory during training.

What's in it?

  1. Generative Adversarial Nets (GAN)
  2. Vanilla GAN
  3. Conditional GAN
  4. InfoGAN
  5. Wasserstein GAN
  6. Mode Regularized GAN
  7. Coupled GAN
  8. Variational Autoencoder (VAE)
  9. Vanilla VAE
  10. Conditional VAE
  11. Denoising VAE
  12. Adversarial Autoencoder
  13. Adversarial Variational Bayes

Dependencies

  1. Install miniconda http://conda.pydata.org/miniconda.html
  2. Do conda env create
  3. Enter the env source activate generative-models
  4. Install Tensorflow
  5. Install Pytorch