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20222026
most citedManifold Learning with Sparse Regularised Optimal Transport

3 citations · 3 across the 11 of their papers we have counts for

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5 papers · 1 filter

math.ST2026

Empirical optimal transport potentials: fast rates and a functional central limit theorem

Alberto González-Sanz, Gilles Mordant, Shunan Sheng

Optimal transport potentials are fundamental objects in statistics, economics, and machine learning: their gradients generate optimal transport maps, while the potentials themselve…

math.ST2025

Estimation of Algebraic Sets: Extending PCA Beyond Linearity

Alberto González-Sanz, Gilles Mordant, Álvaro Samperio +1

An algebraic set is defined as the zero locus of a system of real polynomial equations. In this paper we address the problem of recovering an unknown algebraic set fr…

math.ST2024

The entropic optimal (self-)transport problem: Limit distributions for decreasing regularization with application to score function estimation

Gilles Mordant

We study the statistical properties of the entropic optimal (self) transport problem for smooth probability measures. We provide an accurate description of the limit distribution f…

math.ST2023

Regularised optimal self-transport is approximate Gaussian mixture maximum likelihood

Gilles Mordant

We investigate the link between regularised self-transport problems and maximum likelihood estimation in Gaussian mixture models (GMM). This link suggests that self-transport follo…

math.ST2022

About limiting spectral distributions of block-rescaled empirical covariance matrices

Gilles Mordant

We establish that the limiting spectral distribution of a block-rescaled empirical covariance matrix is an arcsine law when the ratio between the dimension and the underlying sampl…