This is an implementation of the work descriped in the ICML 2017 workshop on implicit models titled "Maximizing Independence with GANs for Non-linear ICA"
ArXiv version (with a slightly different title): [https://arxiv.org/abs/1710.05050]
- numpy, tensorflow, visdom
- matplotlib for plotting results
- scipy for reading the audio data
- the audio data itself
Clone the repository and you should be good to go.
First, start a visdom server using python -m visdom.server for visualizing the results.
Next, run python train.py -c ./examples/gan_mlp_example.conf --vd_server=http://127.0.0.1
to train a model with the settings from one of the example configurations.
The settings in the configuration files can be overridden using the command line.
python train.py -h will print the available command line and configuration options.
The folder ./examples/best contains the hyper-parameters found using a random search.
MIT