Need help with generative-models?
Click the “chat” button below for chat support from the developer who created it, or find similar developers for support.

About the developer

wiseodd
6.5K Stars 2.0K Forks The Unlicense 111 Commits 19 Opened issues

Description

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

Services available

!
?

Need anything else?

Contributors list

# 1,042
Python
Tensorf...
pytorch
generat...
96 commits
# 13,705
Python
Tensorf...
pytorch
rbm
5 commits
# 17,218
pytorch
Jupyter...
Ruby
TeX
1 commit
# 38,689
CSS
Tensorf...
pytorch
rbm
1 commit
# 38,948
Tensorf...
pytorch
rbm
restric...
1 commit
# 38,421
Tensorf...
pytorch
rbm
restric...
1 commit

Generative Models

Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow. Also present here are RBM and Helmholtz Machine.

Note:

Generated samples will be stored in

GAN/{gan_model}/out
(or
VAE/{vae_model}/out
, etc) directory during training.

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
  14. Adversarial Feature Learning & Adversarially Learned Inference
  15. Boundary Equilibrium GAN
  16. Improved Training for Wasserstein GAN
  17. DualGAN
  18. MAGAN: Margin Adaptation for GAN
  19. Softmax GAN
  20. GibbsNet

Variational Autoencoder (VAE)

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

Restricted Boltzmann Machine (RBM)

  1. Binary RBM with Contrastive Divergence
  2. Binary RBM with Persistent Contrastive Divergence

Helmholtz Machine

  1. Binary Helmholtz Machine with Wake-Sleep Algorithm

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

We use cookies. If you continue to browse the site, you agree to the use of cookies. For more information on our use of cookies please see our Privacy Policy.