VAE-WGAN-GP

• This is a Variational Auto-encoder Wasserstein Generative Adverserial Networks Gradient Penalty implementation in tensorflow.
• It is based on the architecture proposed in original VAEGAN paper: https://arxiv.org/abs/1512.09300 .
• WGAN and GP implementations are based on: https://keras.io/examples/generative/wgan_gp/ .
• Encoder, Decoder and Discriminator networks exists in the code to be an example.
• You can simply initialize VAEWGANGP class and .fit() .