$\texttt{skwdro}$: a library for Wasserstein distributionally robust machine learning

Understand

We present skwdro, a Python library for training robust machine learning models.

• The library is based on distributionally robust optimization using Wasserstein distances, popular in optimal transport and machine learnings.
• The goal of the library is to make the training of robust models easier for a wide audience by proposing a wrapper for PyTorch modules, enabling model loss' robustification with minimal code changes.
• It comes along with scikit-learn compatible estimators for some popular objectives.