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Related papers: Generalized Wasserstein Barycenters

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In this note we consider the stability of posterior measures occuring in Bayesian inference w.r.t. perturbations of the prior measure and the log-likelihood function. This extends the well-posedness analysis of Bayesian inverse problems. In…

Statistics Theory · Mathematics 2020-06-24 Björn Sprungk

The consensus problem -- achieving agreement among a network of agents -- is a central theme in both theory and applications. Recently, this problem has been extended from Euclidean spaces to the space of probability measures, where the…

Optimization and Control · Mathematics 2025-10-01 Pilgyu Jung , Yoon Mo Jung

We study the complexity of approximating Wassertein barycenter of $m$ discrete measures, or histograms of size $n$ by contrasting two alternative approaches, both using entropic regularization. The first approach is based on the Iterative…

Optimization and Control · Mathematics 2020-02-21 Alexey Kroshnin , Darina Dvinskikh , Pavel Dvurechensky , Alexander Gasnikov , Nazarii Tupitsa , Cesar Uribe

We establish conditions to characterize probability measures by their $L^{p}$-quantization error functions in both $\mathbb{R}^{d}$ and Hilbert settings. This characterization is two-fold: static (identity of two distributions) and dynamic…

Probability · Mathematics 2020-02-20 Yating Liu , Gilles Pagès

We extend the notion of conformal barycenter, recently introduced by Ja\v{c}imovi\'{c} and Kalaj for the complex hyperbolic ball, to the quaternionic unit ball $\BH$. The quaternionic conformal barycenter of a measurable set $D$ with finite…

Mathematical Physics · Physics 2026-05-21 Wensheng Cao , Zhijian Ge

This paper presents a unified computational framework for the estimation of distances, geodesics and barycenters of merge trees. We extend recent work on the edit distance [106] and introduce a new metric, called the Wasserstein distance…

Graphics · Computer Science 2021-09-21 Mathieu Pont , Jules Vidal , Julie Delon , Julien Tierny

The Wasserstein distance provides a notion of dissimilarities between probability measures, which has recent applications in learning of structured data with varying size such as images and text documents. In this work, we study the…

Machine Learning · Statistics 2022-06-28 Donlapark Ponnoprat

We give a survey, known and new results on the beingness of fixed points of the maximal operator in the more general settings of metric measure space. In particular, we prove that the fixed points of the uncentered one must be the constant…

Metric Geometry · Mathematics 2022-11-29 Wu-yi Pan

We construct two minimal Cheeger sets in the Euclidean plane, i.e. unique minimizers of the ratio "perimeter over area" among their own measurable subsets. The first one gives a counterexample to the so-called weak regularity property of…

Analysis of PDEs · Mathematics 2018-08-30 Gian Paolo Leonardi , Giorgio Saracco

A metric probability space $(\Omega,d)$ obeys the ${\it concentration\; of\; measure\; phenomenon}$ if subsets of measure $1/2$ enlarge to subsets of measure close to 1 as a transition parameter $\epsilon$ approaches a limit. In this paper…

Probability · Mathematics 2024-08-07 Jonathan Root , Mark Kon

The Wasserstein metric is an important measure of distance between probability distributions, with applications in machine learning, statistics, probability theory, and data analysis. This paper provides upper and lower bounds on…

Statistics Theory · Mathematics 2019-11-11 Shashank Singh , Barnabás Póczos

Optimal transport is a notoriously difficult problem to solve numerically, with current approaches often remaining intractable for very large scale applications such as those encountered in machine learning. Wasserstein barycenters -- the…

Machine Learning · Computer Science 2021-02-25 Julien Lacombe , Julie Digne , Nicolas Courty , Nicolas Bonneel

We obtain essentially matching upper and lower bounds for the expected max-sliced 1-Wasserstein distance between a probability measure on a separable Hilbert space and its empirical distribution from $n$ samples. By proving a Banach space…

Probability · Mathematics 2024-11-27 March T. Boedihardjo

In this paper, we establish sharp upper and lower bounds on the convergence rate of the empirical measures of point processes under the Wasserstein distance. To this end, we first introduce a new metric on the space of counting measures…

Statistics Theory · Mathematics 2026-04-28 Dongzhou Huang , Tianyi Jiang , Haonan Wang

This paper deals with the problem of quantifying the approximation a probability measure by means of an empirical (in a wide sense) random probability measure, depending on the first n terms of a sequence of random elements. In Section 2,…

Probability · Mathematics 2018-08-23 Emanuele Dolera , Eugenio Regazzini

The Wasserstein distance between two probability measures on a metric space is a measure of closeness with applications in statistics, probability, and machine learning. In this work, we consider the fundamental question of how quickly the…

Probability · Mathematics 2017-07-04 Jonathan Weed , Francis Bach

In this article we introduce a quasiprobability distribution of work that is based on the Wigner function. This construction rests on the idea that the work done on an isolated system can be coherently measured by coupling the system to a…

Quantum Physics · Physics 2023-11-03 Federico Cerisola , Franco Mayo , Augusto J. Roncaglia

We prove an inequality on the Kantorovich-Rubinstein distance --which can be seen as a particular case of a Wasserstein metric-- between two solutions of the spatially homogeneous Boltzmann equation without angular cutoff, but with a…

Analysis of PDEs · Mathematics 2010-02-02 Nicolas Fournier , Clément Mouhot

A class of signed joint probability measures for n arbitrary quantum observables is derived and studied based on quasi-characteristic functions with symmetrized operator orderings of Margenau-Hill type. It is shown that the Wigner…

Quantum Physics · Physics 2024-10-01 Ralph Sabbagh , Olga Movilla Miangolarra , Hamid Hezari , Tryphon T. Georgiou

We prove the existence of a continuous $BV$ minimizer with $C^{0}$ boundary value for the $p$-area (pseudohermitian or horizontal area) in a parabolically convex bounded domain. We extend the domain of the area functional from $BV$…

Analysis of PDEs · Mathematics 2011-02-15 Jih-Hsin Cheng , Jenn-Fang Hwang