2 citations · 2 across the 6 of their papers we have counts for
8 papers
A central limit theorem for the random assignment problem
Gilles Mordant
Let \(C_n\) be the minimum cost of a perfect matching in an \(n\times n\) matrix of independent uniform random variables. We prove that \[ \sqrt n\{C_n-ζ(2)\} \ \Longrightarrow\ \m…
p-Wasserstein distances on networks and 3D to 1D convergence
Martin Burger, Ariane Fazeny, Gilles Mordant +1
We study transport distances on metric graphs representing gas networks. Starting from the dynamic formulation of the Wasserstein distance, we review extensions to networks, with a…
Quantifying the noise sensitivity of the Wasserstein metric for images
Erik Lager, Gilles Mordant, Amit Moscovich
Wasserstein metrics are increasingly adopted as similarity scores for images. We consider the sensitivity of Wasserstein metrics with respect to pixel-wise additive noise when the…
Center-Outward Multiple-Output Lorenz Curves and Gini Indices a measure transportation approach
Marc Hallin, Gilles Mordant
Based on measure transportation ideas and the related concepts of center-outward quantile functions, we propose multiple-output center-outward generalizations of the traditional un…
On the Finite-Sample Performance of Measure Transportation-Based Multivariate Rank Tests
Marc Hallin, Gilles Mordant
Extending to dimension 2 and higher the dual univariate concepts of ranks and quantiles has remained an open problem for more than half a century. Based on measure transportation r…
Measuring dependence between random vectors via optimal transport
Gilles Mordant, Johan Segers
To quantify the dependence between two random vectors of possibly different dimensions, we propose to rely on the properties of the 2-Wasserstein distance. We first propose two coe…
Maxima and near-maxima of a Gaussian random assignment field
Gilles Mordant, Johan Segers
The assumption that the elements of the cost matrix in the classical assignment problem are drawn independently from a standard Gaussian distribution motivates the study of a parti…
Multivariate goodness-of-Fit tests based on Wasserstein distance
Marc Hallin, Gilles Mordant, Johan Segers
Goodness-of-fit tests based on the empirical Wasserstein distance are proposed for simple and composite null hypotheses involving general multivariate distributions. For group fami…