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.
It's important to note that Python 3.11 was used for this project, particularly for compatibility with the PyTorch library, so we recommend using this version.
1. To install Python 3.11, we recommend using Anaconda, by executing the following command:
Details of the experiments are given in the [Jupiter Notebook](./notebook.ipynb). However, they can be reproduced simply by executing the following commands: