This project consisted in studying GANs in the case of Wasserstein distance, as part of the fifth-year course at INSA Toulouse in Applied Mathematics of High Dimensional and Deep Learning.

GAN python scholarship

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README.md

Wasserstein GAN

This project is based on the following resources:

Paper: Wasserstein GAN
GitHub: martinarjovsky/WassersteinGAN

Use

python main.py --dataset folder --dataroot data/maps