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

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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. Auxiliary Classifier GAN
  9. Least Squares GAN
  10. Boundary Seeking GAN
  11. Variational Autoencoder (VAE)
  12. Vanilla VAE
  13. Conditional VAE
  14. Denoising VAE
  15. Adversarial Autoencoder
  16. 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

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

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  • Python 100.0%