yoonsj/generative-models

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

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