The relevant blog post is here: http://hjweide.github.io/adversarial-autoencoders

A Lasagne and Theano implementation of the paper Adversarial Autoencoders by Alireza Makhzani, Jonathon Shlens, Navdeep Jaitly, and Ian Goodfellow.

Several design choices were made based on the discussion on [/r/machinelearning](https://www.reddit.com/r/MachineLearning/comments/3ybj4d/151105644_adversarial_autoencod ers/?).

To use this code:

1. Download the MNIST data files.
2. Unzip and copy to the mnist directory.
3. Run python train.py to train a model, the weights will be saved to the weights directory.
4. Run python plot.py to generate the visualizations.

Sample images generated by traversing the latent space of the adversarial autoencoder: