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Motivated by a question of Tsai-Tsui-Wang, we consider the rigidity of map from manifolds with positive Ricci curvature to manifolds with positive sectional curvature. We show that if the Ricci curvature of the domain dominates that of the…

Differential Geometry · Mathematics 2024-11-25 Man-Chun Lee , Jingbo Wan

In this paper we consider a random walk of a particle in $\mathbb{R}^d$. Convergence of different transformations of trajectories of random flights with Poisson switching moments has been obtained by Davydov and Konakov, as well as…

Probability · Mathematics 2019-10-10 Alexander Falaleev , Valentin Konakov

We provide upper bounds of the expected Wasserstein distance between a probability measure and its empirical version, generalizing recent results for finite dimensional Euclidean spaces and bounded functional spaces. Such a generalization…

Statistics Theory · Mathematics 2020-01-29 Jing Lei

This article provides a case study for a recently introduced diffusion in the space of probability measures over the reals, namely rearranged stochastic heat, which solves a stochastic partial differential equation valued in the set of…

Probability · Mathematics 2024-06-11 François Delarue , William R. P. Hammersley

We introduce the Langevin deformation for the R\'enyi entropy on the $L^2$-Wasserstein space over $\mathbb{R}^n$ or a Riemannian manifold, which interpolates between the porous medium equation and the Benamou-Brenier geodesic flow on the…

Probability · Mathematics 2024-10-29 Rong Lei , Songzi Li , Xiang-Dong Li

On a smooth (not necessarily compact) manifold $M$ equipped with a $\sf C^1$-family of complete Riemannian metrics $g(t)$ and a $\sf C^{1,\infty}$-family of vector fields $Z(t)$ both indexed by the real interval $[0,T)$ where $T \in…

Probability · Mathematics 2024-03-06 Robert Baumgarth

We address the estimation problem for general finite mixture models, with a particular focus on the elliptical mixture models (EMMs). Compared to the widely adopted Kullback-Leibler divergence, we show that the Wasserstein distance provides…

Machine Learning · Computer Science 2020-10-09 Shengxi Li , Zeyang Yu , Min Xiang , Danilo Mandic

We study the problem of finding the global Riemannian center of mass of a set of data points on a Riemannian manifold. Specifically, we investigate the convergence of constant step-size gradient descent algorithms for solving this problem.…

Differential Geometry · Mathematics 2012-01-05 Bijan Afsari , Roberto Tron , René Vidal

In this paper, we use the information-theoretic approach to study curvature-dimension condition, rigidity theorems and entropy differential inequalities on Riemannian manifolds. We prove the equivalence of the ${\rm CD}(K, m)$-condition for…

Differential Geometry · Mathematics 2026-03-06 Xiang-Dong Li

In this paper, we prove the concavity of the Shannon entropy power for the heat equation associated with the Laplacian or the Witten Laplacian on complete Riemannian manifolds with suitable curvature-dimension condition and on compact super…

Differential Geometry · Mathematics 2020-01-03 S. Li , X. -D. Li

In this paper, we deal with a class of time-homogeneous continuous-time Markov processes with transition probabilities bearing a nonparametric uncertainty. The uncertainty is modeled by considering perturbations of the transition…

Probability · Mathematics 2022-04-11 Sven Fuhrmann , Michael Kupper , Max Nendel

We elaborate the notion of a Ricci curvature lower bound for parametrized statistical models. Following the seminal ideas of Lott-Strum-Villani, we define this notion based on the geodesic convexity of the Kullback-Leibler divergence in a…

Statistics Theory · Mathematics 2021-01-05 Wuchen Li , Guido Montufar

We investigate proximal descent methods, inspired by the minimizing movement scheme introduced by Jordan, Kinderlehrer and Otto, for optimizing entropy-regularized functionals on the Wasserstein space. We establish linear convergence under…

Optimization and Control · Mathematics 2024-11-25 Razvan-Andrei Lascu , Mateusz B. Majka , David Šiška , Łukasz Szpruch

In this paper, we obtain quantitative, non-asymptotic, and data-dependent \textit{Bernstein-von Mises type} bounds on the normal approximation of the posterior distribution in exponential family models with arbitrary centring and scaling.…

Statistics Theory · Mathematics 2025-01-14 Adrian Fischer , Robert E. Gaunt , Gesine Reinert , Yvik Swan

We construct a recurrent diffusion process with values in the space of probability measures over an arbitrary closed Riemannian manifold of dimension $d\ge 2$. The process is associated with the Dirichlet form defined by integration of the…

Probability · Mathematics 2022-04-04 L. Dello Schiavo

Discrete diffusion models have emerged as a powerful paradigm for generative modeling on sequence data; however, the information-theoretic principles governing their reverse processes remain significantly less understood than those of their…

Machine Learning · Computer Science 2026-02-10 Alberto Foresti , Mustapha Bounoua , Giulio Franzese , Luca Ambrogioni , Pietro Michiardi

Given two continuity equations with density-dependent velocities, we provide a new formula for the Wasserstein distance between the solutions in terms of the difference of velocities evaluated at the same density. The formula is…

Analysis of PDEs · Mathematics 2026-03-27 José A. Carrillo , Piotr Gwiazda , Jakub Skrzeczkowski

This survey reviews some facts about nonnegativity conditions on the curvature tensor of a Riemannian manifold which are preserved by the action of the Ricci flow. The text focuses on two main points. First we describe the known examples of…

Differential Geometry · Mathematics 2014-11-21 Thomas Richard

Neuron models have attracted a lot of attention recently, both in mathematics and neuroscience. We are interested in studying long-time and large-population emerging properties in a simplified toy model. From a mathematical perspective,…

Probability · Mathematics 2024-01-31 Maxime Herda , Pierre Monmarché , Benoît Perthame

We study the discretization of generalized Wasserstein distances with nonlinear mobilities on the real line via suitable discrete metrics on the cone of N ordered particles, a setting which naturally appears in the framework of…

Analysis of PDEs · Mathematics 2022-09-01 Simone Di Marino , Lorenzo Portinale , Emanuela Radici