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A new approach to disintegration of measures is presented, allowing one to drop the usually taken separability assumption. The main tool is a result on fibers in the spectrum of algebra of essentially bounded functions established recently…

Functional Analysis · Mathematics 2023-04-06 Marek Kosiek , Krzysztof Rudol

The problem of quantization of measures looks for best approximations of probability measures on a metric space by discrete measures supported on $N$ points, where the error of approximation is measured with respect to the Wasserstein…

Metric Geometry · Mathematics 2026-02-17 Ata Deniz Aydin

Conditioning, the central operation in Bayesian statistics, is formalised by the notion of disintegration of measures. However, due to the implicit nature of their definition, constructing disintegrations is often difficult. A folklore…

Statistics Theory · Mathematics 2025-08-04 Nathaël Da Costa , Marvin Pförtner , Jon Cockayne

We introduce the basic concepts related to subharmonic functions and potentials, mainly for the case of the complex plane and prove the Riesz decomposition theorem. Beyond the elementary facts of the theory we deviate slightly from the…

Classical Analysis and ODEs · Mathematics 2008-05-01 Christian Kuehn

In this article, we propose a general framework for the study of differential inclusions in the Wasserstein space of probability measures. Based on earlier geometric insights on the structure of continuity equations, we define solutions of…

Optimization and Control · Mathematics 2020-07-28 Benoît Bonnet , Hélène Frankowska

Given a complete Riemannian manifold $M$ with a lower Ricci curvature bound, we consider barycenters in the Wasserstein space $\mathcal{W}_2(M)$ of probability measures on $M$. We refer to them as Wasserstein barycenters, which by…

Probability · Mathematics 2025-12-05 Jianyu Ma

Symmetry is a cornerstone of much of mathematics, and many probability distributions possess symmetries characterized by their invariance to a collection of group actions. Thus, many mathematical and statistical methods rely on such…

Statistics Theory · Mathematics 2023-10-23 Adam B Kashlak

We introduce the observable Wasserstein distance, a framework for deriving lower bounds on the Wasserstein distance between probability measures on Polish metric spaces, designed to bypass the computational intractability of exact optimal…

Metric Geometry · Mathematics 2026-05-12 Edivaldo Lopes dos Santos , Leandro Vicente Mauri , Washington Mio , Tom Needham

We consider the problem of estimating smooth integrated functionals of a monotone nonincreasing density $f$ on $[0,\infty)$ using the nonparametric maximum likelihood based plug-in estimator. We find the exact asymptotic distribution of…

Statistics Theory · Mathematics 2019-04-16 Rajarshi Mukherjee , Bodhisattva Sen

Goodness-of-fit tests based on the empirical Wasserstein distance are proposed for simple and composite null hypotheses involving general multivariate distributions. For group families, the procedure is to be implemented after preliminary…

Methodology · Statistics 2021-01-28 Marc Hallin , Gilles Mordant , Johan Segers

We introduce principal curves in Wasserstein space, and in general compact metric spaces. Our motivation for the Wasserstein case comes from optimal-transport-based trajectory inference, where a developing population of cells traces out a…

Statistics Theory · Mathematics 2025-05-08 Andrew Warren , Anton Afanassiev , Forest Kobayashi , Young-Heon Kim , Geoffrey Schiebinger

The empirical distribution function assigns mass $1/n$ to each of the $n$ observations in a sample. As these are highly variable, estimation error may be reduced by replacing them with estimated observations that are asymptotically less…

Methodology · Statistics 2026-05-26 Tommaso Lando , Lorenzo Tedesco

We analyze the reducibilities induced by, respectively, uniformly continuous, Lipschitz, and nonexpansive functions on arbitrary ultrametric Polish spaces, and determine whether under suitable set-theoretical assumptions the induced…

Logic · Mathematics 2013-10-29 Luca Motto Ros , Philipp Schlicht

We consider a logic with truth values in the unit interval and which uses aggregation functions instead of quantifiers, and we describe a general approach to asymptotic elimination of aggregation functions and, indirectly, of asymptotic…

Logic · Mathematics 2026-05-28 Vera Koponen , Felix Weitkämper

The asymptotic behavior for fully coupled multiscale stochastic systems becomes much complicated when the fast processes do not locate in a compact space. An example is constructed to show that the averaged coefficients may become…

Probability · Mathematics 2025-09-23 Shen Wang , Jinghai Shao

We quantify Prokhorov's Theorem by establishing an explicit formula for the Hausdorff measure of non-compactness (HMNC) for the parametrized Prokhorov metric on the set of Borel probability measures on a Polish space. Furthermore, we…

Probability · Mathematics 2016-08-01 Ben Berckmoes

We propose of an improved version of the ubiquitous symmetrization inequality making use of the Wasserstein distance between a measure and its reflection in order to quantify the symmetry of the given measure. An empirical bound on this…

Statistics Theory · Mathematics 2020-01-07 Adam B Kashlak

The classical Erd\H{o}s-Tur\'an inequality on the distribution of roots for complex polynomials can be equivalently stated in a potential theoretic formulation, that is, if the logarithmic potential generated by a probability measure on the…

Classical Analysis and ODEs · Mathematics 2021-10-08 Ruiwen Shu , Jiuya Wang

In this paper, we study a connection between disintegration of measures and geometric properties of probability spaces. We prove a disintegration theorem, addressing disintegration from the perspective of an optimal transport problem. We…

Probability · Mathematics 2025-04-09 Renata Possobon , Christian S. Rodrigues

The notions of disintegration and Bayesian inversion are fundamental in conditional probability theory. They produce channels, as conditional probabilities, from a joint state, or from an already given channel (in opposite direction). These…

Artificial Intelligence · Computer Science 2019-07-31 Kenta Cho , Bart Jacobs
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