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.
- Generative Adversarial Nets (GAN)
- Vanilla GAN
- Conditional GAN
- InfoGAN
- Wasserstein GAN
- Mode Regularized GAN
- Coupled GAN
- Auxiliary Classifier GAN
- Least Squares GAN
- Boundary Seeking GAN
- Variational Autoencoder (VAE)
- Vanilla VAE
- Conditional VAE
- Denoising VAE
- Adversarial Autoencoder
- Adversarial Variational Bayes
- Install miniconda http://conda.pydata.org/miniconda.html
- Do
conda env create
- Enter the env
source activate generative-models
- Install Tensorflow
- Install Pytorch