Tools for Computational Optimal Transport
Barycenter of Empirical CDFs
Wasserstein Median of Empirical CDFs
Fixed-Support Barycenter by Cuturi & Doucet (2014)
Fixed-Support Barycenter by Benamou et al. (2015)
Compute the fiedler vector of a point cloud
Barycenter of Gaussian Distributions in
Barycenter of Gaussian Distributions in
Wasserstein Median of Gaussian Distributions in
Wasserstein Median of Gaussian Distributions in
Sampling from a Bivariate Gaussian Distribution for Visualization
Gromov-Wasserstein Barycenter
Gromov-Wasserstein Distance
Barycenter of Histograms
Barycenter of Histograms by Cuturi and Doucet (2014)
Barycenter of Histograms by Benamou et al. (2015)
Distance between Histograms
Interpolation between Histograms
Wasserstein Median of Histograms
Barycenter of Images
Barycenter of Images according to Cuturi & Doucet (2014)
Barycenter of Images according to Benamou et al. (2015)
Wasserstein Distance between Two Images
Interpolation between Images
Wasserstein Median of Images
Extract a discrete measure from a gray-scale image matrix
Wasserstein Distance via Inexact Proximal Point Method
Procrustes-Wasserstein Barycenter
Procrustes-Wasserstein Distance
Free-Support Barycenter by von Lindheim (2023)
Free-Support Barycenter by Riemannian Gradient Descent
Free-Support Median by IRLS
Free-Support Median by Weiszfeld Update with Barycentric Projection
Wasserstein Distance via Entropic Regularization and Sinkhorn Algorith...
Sliced Wasserstein Distance
Wasserstein Distance Estimation with Boostrapping
Wasserstein Distance via Linear Programming
Transport theory has seen much success in many fields of statistics and machine learning. We provide a variety of algorithms to compute Wasserstein distance, barycenter, and others. See Peyré and Cuturi (2019) <doi:10.1561/2200000073> for the general exposition to the study of computational optimal transport.