Skip to content

About

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

Resources

Stars

0 stars

Watchers

0 watching

Forks

 
 

Latest commit

 

History

65 Commits

Folders and files

NameName
Last commit message
Last commit date
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Generative Models

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

Note:

  1. Generated samples will be stored in GAN/{gan_model}/out or VAE/{vae_model}/out directory during training.
  2. If your TensorFlow version is v1.0+, run *_tensorflow_v1.py scripts instead of *_tensorflow.py.

What's in it?

Generative Adversarial Nets (GAN)

  1. Vanilla GAN
  2. Conditional GAN
  3. InfoGAN
  4. Wasserstein GAN
  5. Mode Regularized GAN
  6. Coupled GAN
  7. Auxiliary Classifier GAN
  8. Least Squares GAN
  9. Boundary Seeking GAN
  10. Energy Based GAN
  11. f-GAN
  12. Generative Adversarial Parallelization
  13. DiscoGAN

Variational Autoencoder (VAE)

  1. Vanilla VAE
  2. Conditional VAE
  3. Denoising VAE
  4. Adversarial Autoencoder
  5. 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

About

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

Resources

Stars

0 stars

Watchers

0 watching

Forks

Releases

Packages

Contributors

Languages