Optimal transport algorithms for Julia

Pseudo-labeling for tabular data

The implementation for the paper "On Unbalanced Optimal Transport: An Analysis of Sinkhorn Algorithm".

🦆 A simple sinkhorn algorithm to solve optimal transport problem writen in Matlab

Sparse simplex projection-based Wasserstein k-means

Python Implementation of "Fast Computation of Wasserstein Barycenters"

[ICML 2023] Official code for our paper: 'Conditional Tree Matching for Inference-Time Adaptation of Tree Prediction Models'

Code for "A MFG Model for the Dynamics of Cities" (Barilla, Carlier, Lasry 2021)

Crowd Counting: A view around state-of-the-art

Unsupervised Domain Adaptation (MNIST -> USPS) using a 'From Scratch' implementation of the Sinkhorn Optimal Transport Algorithm.

Unofficial implementation of the paper 'Sinkhorn Solves Sudoku' in C with Python starter code

High-performance Python package for balanced k-means clustering using optimal transport and entropic regularization

Python translation of Cuturi's MATLAB code for Sinkhorn Optimal Transport.

三维张量 Sinkhorn-Knopp 连续松弛求解数独。将数独视为 9×9×9 概率张量连续优化问题，通过熵减和交替投影到四个约束集求解，无需搜索树或约束传播。含 Phistomefel 环计算分析。

Computational optimal transport

anyakrakusuma is a high-performance Python solver for the 2D Schrödinger Bridge Problem via Entropic Optimal Transport (EOT), utilizing the log-domain Sinkhorn-Knopp algorithm and Numba acceleration for robust stochastic process interpolation.

Optimal transport distances