nahumsa/Variational-Autoencoder

Notebooks with examples using variational autoencoders.

Variational Autoencoder

In order to use the code on this repository, install the dependencies using conda:

• conda env create -f environment.yml

• source activate VAE_env

To put this environtmen on your jupyter notebook environment you need to type the following comands:

• conda install jupyter

• conda install nb_conda

• conda install ipykernel

• python -m ipykernel install --user --name VAE_env

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Examples using a (Beta-)Variational autoencoder.

• MNIST with Beta-Variational Autoencoder using Tensorflow

• MNIST with Beta-Variational Autoencoder using Keras.

• Dsprites with Variational Autoencoder using Keras

• Dsprites traversals with Variational Autoencoder using Keras

• Dsprites positions with Variational Autoencoder using Keras

• Representing Qubits using Beta-Variational autoencoder