Wasserstein Distance Using C# and Python. μ ¯ = argmin μ ∈ P 2 ( θ) ∑ t = 1 T α t W 2 2 ( μ, μ t), where α ∈ R T is a weight vector that sums to 1. GitHub. The q-Wasserstein distance is defined as the minimal value achieved by a perfect matching between the points of the two diagrams (+ all diagonal points), where the value of a matching is defined as the q-th root of the sum of all edge lengths to the power q. scipy - Is there a way to measure the distance between two ... Earth mover's distance Gaussian Processes Barycentres - GPJax 0.4.6 documentation All experiments are run on a … Multivariate approximations in Wasserstein distance by Stein’s … Goodness-of-fit tests based on the empirical Wasserstein distance are proposed for simple and composite null hypotheses involving general multivariate distributions. Wasserstein Distance Wasserstein
