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5 papers

stat.ML2026

Convergence Rates for Distribution Matching with Sliced Optimal Transport

Gauthier Thurin, Claire Boyer, Kimia Nadjahi

The paper analyzes an iterative sliced optimal transport method for matching probability distributions, providing non‑asymptotic convergence rates and showing how the method behave…

stat.ME2026

Regularized estimation of Monge-Kantorovich quantiles for spherical data

Bernard Bercu, Jérémie Bigot, Gauthier Thurin

Tools from optimal transport (OT) theory have recently been used to define a notion of quantile function for directional data. In practice, regularization is mandatory for applicat…

math.PR2025

Stochastic optimal transport in Banach Spaces for regularized estimation of multivariate quantiles

Bernard Bercu, Jérémie Bigot, Gauthier Thurin

We introduce a new stochastic algorithm for solving entropic optimal transport (EOT) between two absolutely continuous probability measures and . Our work is motivated by…

stat.ML2025

Optimal Transport-based Conformal Prediction

Gauthier Thurin, Kimia Nadjahi, Claire Boyer

Conformal Prediction (CP) is a principled framework for quantifying uncertainty in blackbox learning models, by constructing prediction sets with finite-sample coverage guarantees.…

stat.ME2025

Monge-Kantorovich quantiles and ranks for image data

Gauthier Thurin

This paper defines quantiles, ranks and statistical depths for image data by leveraging ideas from measure transportation. The first step is to embed a distribution of images in a…