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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 propose a new notion of the formal tangent space to the Wasserstein space $\mathcal{P}(X)$ at a given measure. Modulo an integrability condition, we say that this tangent space is made of functions over $X$ which are valued in the…

Analysis of PDEs · Mathematics 2025-12-11 Charles Bertucci

We discuss the relation between the Wasserstein distance of order 1 between probability distributions on a metric space, arising in the study of Monge-Kantorovich transport problem, and the spectral distance of noncommutative geometry.…

Operator Algebras · Mathematics 2015-03-13 Francesco D'Andrea , Pierre Martinetti

We study the quantitative convergence of drift-diffusion PDEs that arise as Wasserstein gradient flows of linearly convex functions over the space of probability measures on ${\mathbb R}^d$. In this setting, the objective is in general not…

Optimization and Control · Mathematics 2025-07-17 Lénaïc Chizat , Maria Colombo , Xavier Fernández-Real

We introduce a class of backward stochastic differential equations (BSDEs) on the Wasserstein space of probability measures. This formulation extends the classical correspondence between BSDEs, stochastic control, and partial differential…

Probability · Mathematics 2025-07-01 Mao Fabrice Djete

We investigate the asymptotic behavior of parametric Bayes estimators under a broad class of loss functions that extend beyond the classical translation-invariant setting. To this end, we develop a unified theoretical framework for loss…

Statistics Theory · Mathematics 2026-03-16 Robin Requadt , Housen Li , Axel Munk

We consider the motion of test particles and light rays in a static cylindrically symmetric conformal spacetime given by Said et al [1]. We derive the equations of motion and present their analytical solutions in terms of the Weierstrass…

General Relativity and Quantum Cosmology · Physics 2016-08-16 Bahareh Hoseini , Reza Saffari , Saheb Soroushfar , Jutta Kunz , Saskia Grunau

Chance constraints yield non-convex feasible regions in general. In particular, when the uncertain parameters are modeled by a Wasserstein ball, arXiv:1806.07418 and arXiv:1809.00210 showed that the distributionally robust (pessimistic)…

Optimization and Control · Mathematics 2025-03-14 Haoming Shen , Ruiwei Jiang

The primary choice to summarize a finite collection of random objects is by using measures of central tendency, such as mean and median. In the field of optimal transport, the Wasserstein barycenter corresponds to the Fr\'{e}chet or…

Methodology · Statistics 2025-09-03 Kisung You , Dennis Shung , Mauro Giuffrè

In this paper, a regularization of Wasserstein barycenters for random measures supported on $\mathbb{R}^{d}$ is introduced via convex penalization. The existence and uniqueness of such barycenters is first proved for a large class of…

Statistics Theory · Mathematics 2019-03-20 Jérémie Bigot , Elsa Cazelles , Nicolas Papadakis

In this note we show that in metric measure spaces satisfying the reduced curvature-dimension condition CD*(K,N) we always have geodesics in the Wasserstein space of probability measures that satisfy the critical convexity inequality of…

Differential Geometry · Mathematics 2012-03-01 Tapio Rajala

The two-sample homogeneity testing problem is fundamental in statistics and becomes particularly challenging in high dimensions, where classical tests can suffer substantial power loss. We develop a learning-assisted procedure based on the…

Methodology · Statistics 2026-01-30 Xiaoyu Hu , Zhenhua Lin

We show from a categorical point of view that probability measures on certain measurable or topological spaces arise canonically as the extension of probability distributions on countable sets. We do this by constructing probability monads…

Category Theory · Mathematics 2022-06-23 Ruben Van Belle

Bayesian methods are developed for the multivariate nonparametric regression problem where the domain is taken to be a compact Riemannian manifold. In terms of the latter, the underlying geometry of the manifold induces certain symmetries…

Statistics Theory · Mathematics 2007-06-13 Jean-François Angers , Peter T. Kim

It is well known that nonlinear diffusion equations can be interpreted as a gradient flow in the space of probability measures equipped with the Euclidean Wasserstein distance. Under suitable convexity conditions on the nonlinearity, due to…

Analysis of PDEs · Mathematics 2014-02-13 François Bolley , José A. Carrillo

We study a class of quadratic Wasserstein distances on spaces consisting of generalized dynamical systems on a von Neumann algebra. We emphasize how symmetry of such a Wasserstein distance arises, but also study the asymmetric case. This…

Operator Algebras · Mathematics 2024-11-05 Rocco Duvenhage

This paper studies the optimization of the KL functional on the Wasserstein space of probability measures, and develops a sampling framework based on Wasserstein gradient descent (WGD). We identify two important subclasses of the…

Computation · Statistics 2026-02-04 Van Chien Ta , Thi Mai Hong Chu , Minh-Ngoc Tran

We prove that for a metric space $X$ and a finite group $G$ acting on $X$ by isometries, if $X$ coarsely embeds into a Hilbert space, then so does the quotient $X/G$. A crucial step towards our main result is to show that for any integer $k…

Metric Geometry · Mathematics 2024-09-05 Thomas Weighill

On a complete, connected, locally compact, non-compact geodesic space $(X,d)$, we assign each compact set a distance-like function. With the help of these functions, we obtain a pseudo-metric on the space of (non-empty) compact subsets of…

Dynamical Systems · Mathematics 2022-02-01 Xiaojun Cui , Liang Jin , Xifeng Su

We consider the fully-coupled McKean-Vlasov equation with multi-time-scale potentials, and all the coefficients depend on the distributions of both the slow component and the fast motion. By studying the smoothness of the solution of the…

Probability · Mathematics 2022-04-28 Yun Li , Fuke Wu , Longjie Xie