1D Generative Adversarial Network Example

Generates a GAN to approximate a 1D Gaussian using the improved Wasserstein GAN (WGAN-GP). Based on the codes from the repositories of Ishaan Gulrajani and AYLIAN and the blog posts by Eric Jang and John Glover.

Running the example

This code uses Python 3.6.1. Install the dependencies via

$ pip install -r requirements.txt

To generate the animated gif, you need to install the ImageMagick library.

To run the code just run

$ python main.py

and it should produce output similar to the animation above.

Name		Name	Last commit message	Last commit date
Latest commit History 5 Commits
README.md		README.md
animation.gif		animation.gif
gan.py		gan.py
main.py		main.py
requirements.txt		requirements.txt