POT : Python Optimal Transport
-
Updated
Dec 17, 2024 - Python
POT : Python Optimal Transport
The Wasserstein Distance and Optimal Transport Map of Gaussian Processes
A Python implementation of Monge optimal transportation
This repo contains the implementation of the Wasserstein Barycenter Transport proposed in "Wasserstein Barycenter Transport for Acoustic Adaptation" at ICASSP21 and "Wasserstein Barycenter for Multi-Source Domain Adaptation" in CVPR21
Efficient Wasserstein Barycenter in MATLAB (for "Fast Discrete Distribution Clustering Using Wasserstein Barycenter with Sparse Support" TSP)
Python Implementation of "Fast Computation of Wasserstein Barycenters"
Wasserstein barycenter research for images
Add a description, image, and links to the wasserstein-barycenters topic page so that developers can more easily learn about it.
To associate your repository with the wasserstein-barycenters topic, visit your repo's landing page and select "manage topics."