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Related papers: Wasserstein Diffusion on Multidimensional Spaces

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We consider a one-dimensional aggregation-diffusion equation, which is the gradient flow in the Wasserstein space of a functional with competing attractive-repulsive interactions. We prove that the fully deterministic particle…

Analysis of PDEs · Mathematics 2021-01-01 Sara Daneri , Emanuela Radici , Eris Runa

Euler and Betti curves of stochastic processes defined on a $d$-dimensional compact Riemannian manifold which are almost surely in a Sobolev space $W^{n,s}(X,\mathbb{R})$ (with $d<n$) are stable under perturbations of the distributions of…

Probability · Mathematics 2022-11-23 Daniel Perez

Optimal Transport (OT) metrics allow for defining discrepancies between two probability measures. Wasserstein distance is for longer the celebrated OT-distance frequently-used in the literature, which seeks probability distributions to be…

Machine Learning · Computer Science 2021-10-14 Mokhtar Z. Alaya , Gilles Gasso , Maxime Berar , Alain Rakotomamonjy

We present a diffeomorphism-invariant formulation of differential entropy for Riemannian spaces, providing a fine-grained, coordinate-independent notion of quantum information for continuous variables in physical space. To this end, we…

Quantum Physics · Physics 2025-05-16 Pablo G. Camara

We prove that the sequence of marginals obtained from the iterations of the Sinkhorn algorithm or the iterative proportional fitting procedure (IPFP) on joint densities, converges to an absolutely continuous curve on the $2$-Wasserstein…

Probability · Mathematics 2026-04-21 Nabarun Deb , Young-Heon Kim , Soumik Pal , Geoffrey Schiebinger

Diffusion generative models have emerged as powerful tools for producing synthetic data from an empirically observed distribution. A common approach involves simulating the time-reversal of an Ornstein-Uhlenbeck (OU) process initialized at…

Machine Learning · Statistics 2025-12-02 Valentin de Bortoli , Romuald Elie , Anna Kazeykina , Zhenjie Ren , Jiacheng Zhang

When the Ricci curvature of a Riemannian manifold is not lower bounded by a constant, but lower bounded by a continuous function, we give a new characterization of this lower bound through the convexity of relative entropy on the…

Probability · Mathematics 2015-07-30 Jinghai Shao , Bo Wu

Given a parabolic cylinder $Q =(0,T)\times\Omega$, where $\Omega\subset \mathbb{R}^{N}$ is a bounded domain, we prove new properties of solutions of \[ u_t-\Delta_p u = \mu \quad \text{in $Q$} \] with Dirichlet boundary conditions, where…

Analysis of PDEs · Mathematics 2025-08-11 Francesco Petitta , Augusto C. Ponce , Alessio Porretta

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

In this work, we establish the existence of solutions to stochastic differential equations on the Wasserstein space over a closed Riemannian manifold, under suitable regularity assumptions on the driving vector fields. Interpreting the…

Probability · Mathematics 2026-03-02 Aymeric Martin

We imagine an experiment on an unknown quantum mechanical system in which the system is prepared in various ways and a range of measurements are performed. For each measurement M and preparation rho the experimenter can determine, given…

Quantum Physics · Physics 2009-01-20 Stephanie Wehner , Matthias Christandl , Andrew C. Doherty

We study the distribution of the magnetization of the critical mean-field O(N) model with N > 1. Specifically, we bound the Wasserstein distance between the finite-volume and limiting distributions, in terms of the number of spins. To…

Probability · Mathematics 2025-12-08 Timothy M. Garoni , Aram Perez , Zongzheng Zhou

In this paper, we propose a modification to the density approach to Stein's method for intervals for the unit circle $\mathbb{S}^1$ which is motivated by the differing geometry of $\mathbb{S}^1$ to Euclidean space. We provide an upper bound…

Probability · Mathematics 2021-05-28 Alexander Lewis

We consider Ising mixed $p$-spin glasses at high-temperature and without external field, and study the problem of sampling from the Gibbs distribution $\mu$ in polynomial time. We develop a new sampling algorithm with complexity of the same…

Probability · Mathematics 2025-10-22 Ahmed El Alaoui , Andrea Montanari , Mark Sellke

We consider in this paper the problem of sampling a high-dimensional probability distribution $\pi$ having a density with respect to the Lebesgue measure on $\mathbb{R}^d$, known up to a normalization constant $x \mapsto \pi(x)=…

Statistics Theory · Mathematics 2018-07-17 Alain Durmus , Eric Moulines

We study the particle method to approximate the gradient flow on the $L^p$-Wasserstein space. This method relies on the discretization of the energy introduced by [3] via nonoverlapping balls centered at the particles and preserves the…

Numerical Analysis · Mathematics 2025-01-08 Rong Lei

This work presents several expected generalization error bounds based on the Wasserstein distance. More specifically, it introduces full-dataset, single-letter, and random-subset bounds, and their analogues in the randomized subsample…

Machine Learning · Statistics 2022-03-29 Borja Rodríguez-Gálvez , Germán Bassi , Ragnar Thobaben , Mikael Skoglund

The problem of reconstructing the drift of a diffusion in $\erre^d$, $d\geq 2$, from the transition probability density observed outside a domain is considered. The solution of this problem also solves a new inverse problem for a class of…

Probability · Mathematics 2007-06-13 Sergio Albeverio , Carlo Marinelli

Let $\lambda$ be a probability measure on $\mathbb T^{n-1}$ where $n=2$ or 3. Suppose $\lambda$ is invariant, ergodic and has positive entropy with respect to the linear transformation defined by a hyperbolic matrix. We get a measure $\mu $…

Dynamical Systems · Mathematics 2014-07-18 Ronggang Shi

Let F ($\nu$) be the centered Gamma law with parameter $\nu$ > 0 and let us denote by P Y the probability distribution of a random vector Y. We develop a multidimensional variant of the Stein's method for Gamma approximation that allows to…

Probability · Mathematics 2023-05-10 Ciprian A Tudor , Jérémy Zurcher