Wasserstein Python Packages

pot

POT : Python Optimal Transport

mat-discover

A materials discovery algorithm geared towards exploring high-performance candidates in new chemical spaces.

wax-ot

WaX: explainable Wasserstein distances. Attributes a Wasserstein distance to instances, features and subspaces (Naumann, Kauffmann and Montavon, TPAMI 2026).

wsingular

Python package for the ICML 2022 paper "Unsupervised Ground Metric Learning Using Wasserstein Singular Vectors".

otloss

Optimal Transport loss functions for PyTorch — Wasserstein, Sliced Wasserstein, and WGAN-GP as drop-in nn.Module replacements

wbtc

Distributional crypto-return forecasting via Wasserstein-geodesic extrapolation in quantile-function space. WGeo family wins 12/12 (asset × horizon) cells over 6.75y walk-forward CRPS vs GARCH and classical baselines. v0.4.