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Implementation of denoise, sparse, contractive, variational autoencoder (VAE) and Beta-VAE in Tensorflow 2.0.

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Autoencoders in TensorFlow 2.0

Implementations of following Autoencoders;

  • Vanilla Autoencoder (AE)
  • Denoise Autoencoder
  • Sparese Autoencoder (in progress)
  • Contractive Autoencoder (in progress)
  • Variational Autoencoder (VAE)
  • Conditional Variational Autoencoder (CVAE)
  • Beat Variational Autoencoder (beta-VAE) (in progress)

How to run:

run python3 main.py --ae_type AE

Parameters that we can pass:

  • ae_type: Type of autoencoder - AE, DAE, VAE, CVAE, BetaVAE
  • latent_dim: Degree of latent dimension - 2, 3, etc.
  • num_epochs: The number of training epochs - 100 etc.
  • learn_rate: Learning rate during training - 1e-4
  • batch_size: Batch size - 1000

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Implementation of denoise, sparse, contractive, variational autoencoder (VAE) and Beta-VAE in Tensorflow 2.0.

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