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We prove a Central Limit Theorem for the empirical optimal transport cost, $\sqrt{\frac{nm}{n+m}}\{\mathcal{T}_c(P_n,Q_m)-\mathcal{T}_c(P,Q)\}$, in the semi discrete case, i.e when the distribution $P$ is supported in $N$ points, but…

Probability · Mathematics 2022-02-15 Eustasio del Barrio , Alberto González-Sanz , Jean-Michel Loubes

Semi-discrete optimal transport problems, which evaluate the Wasserstein distance between a discrete and a generic (possibly non-discrete) probability measure, are believed to be computationally hard. Even though such problems are…

Machine Learning · Computer Science 2022-05-02 Bahar Taskesen , Soroosh Shafieezadeh-Abadeh , Daniel Kuhn

The Wasserstein distance quantifies the distance between two probability measures on a metric space. We prove an analogue of the Berry-Esseen inequality for the Wasserstein distance on a finite area hyperbolic surface. This inequality…

Number Theory · Mathematics 2025-12-18 Peter Humphries

Distances between probability distributions that take into account the geometry of their sample space,like the Wasserstein or the Maximum Mean Discrepancy (MMD) distances have received a lot of attention in machine learning as they can, for…

Machine Learning · Computer Science 2020-04-29 Gaëtan Hadjeres , Frank Nielsen

We establish some deviation inequalities, moment bounds and almost sure results for the Wasserstein distance of order p $\in$ [1, $\infty$) between the empirical measure of independent and identically distributed R d-valued random variables…

Probability · Mathematics 2018-12-21 Jérôme Dedecker , Florence Merlevède

Constrained diffusions in convex polyhedral domains with a general oblique reflection field, and with a diffusion coefficient scaled by a small parameter, are considered. Using an interior Dirichlet heat kernel lower bound estimate for…

Probability · Mathematics 2013-08-19 Amarjit Budhiraja , Zhen-Qing Chen

We suggest the diffuse approach to the relaxation processes within the kinetic theory for the Wigner distribution function. The diffusion and drift coefficients are evaluated taking into consideration the interparticle collisions on the…

Nuclear Theory · Physics 2015-04-02 V. M. Kolomietz , S. V. Lukyanov

We extend the celebrated Stone's theorem to the framework of distributional regression. More precisely, we prove that weighted empirical distribution with local probability weights satisfying the conditions of Stone's theorem provide…

Statistics Theory · Mathematics 2023-02-03 Clément Dombry , Thibault Modeste , Romain Pic

In graphs and Riemannian manifolds where the kernel of the diffusion semigroup satisfies pointwise sub-Gaussian estimates, we study the range of parameters \( p \in (1, \infty) \) and \( \gamma \in [0, 1] \) for which the quantities \(…

Functional Analysis · Mathematics 2025-08-15 Joseph Feneuil

Let $E/\mathbb{Q}$ be an elliptic curve and let $p$ be a prime of good supersingular reduction. Attached to $E$ are pairs of Iwasawa invariants $\mu_p^\pm$ and $\lambda_p^\pm$ which encode arithmetic properties of $E$ along the cyclotomic…

Number Theory · Mathematics 2025-01-29 Rylan Gajek-Leonard

Under general assumptions on the target distribution $p^\star$, we establish a sharp Lipschitz regularity theory for flow-matching vector fields and diffusion-model scores, with optimal dependence on time and dimension. As applications, we…

Statistics Theory · Mathematics 2026-04-08 Arthur Stéphanovitch

We show that the sectional curvature of a Riemannian manifold is nonnegative if, and only if, the entropy functional is matrix displacement convex. As an application we obtain intrinsic dimensional evolution variational inequalities, and…

Differential Geometry · Mathematics 2025-09-30 Gautam Aishwarya , Liran Rotem , Yair Shenfeld

Score-based generative modeling with probability flow ordinary differential equations (ODEs) has achieved remarkable success in a variety of applications. While various fast ODE-based samplers have been proposed in the literature and…

Machine Learning · Statistics 2025-08-12 Xuefeng Gao , Lingjiong Zhu

Consider the class of zero-mean functions with fixed $L^{\infty}$ and $L^1$ norms and exactly $N\in \mathbb{N}$ nodal points. Which functions $f$ minimize $W_p(f_+,f_-)$, the Wasserstein distance between the measures whose densities are the…

Classical Analysis and ODEs · Mathematics 2023-06-26 Qiang Du , Amir Sagiv

We employ techniques from optimal transport in order to prove decay of transfer operators associated to iterated functions systems and expanding maps, giving rise to a new proof without requiring a Doeblin-Fortet (or Lasota-Yorke)…

Dynamical Systems · Mathematics 2015-08-25 Benoit Kloeckner , Artur Lopes , Manuel Stadlbauer

We study the pairing potential induced by fluctuations around a charge-density wave (CDW) with scattering vector Q by means of the Froehlich transformation. For general commensurability M, defined as |k+M*Q>=|k>, we find that the intraband…

Superconductivity · Physics 2009-10-31 G. Seibold , S. Varlamov

We prove $L^p$-Hardy inequalities with distance to the boundary for domains in the Heisenberg group ${\mathbb{H}}^n$, $n\geq 1$. Our results are based on a certain geometric condition. This is first implemented for the Euclidean distance in…

Analysis of PDEs · Mathematics 2026-03-24 Gerassimos Barbatis , Marianna Chatzakou , Achilles Tertikas

In the paper we prove two inequalities in the setting of ${\sf RCD}(K,\infty)$ spaces using similar techniques. The first one is an indeterminacy estimate involving the $p$-Wasserstein distance between the positive part and the negative…

Differential Geometry · Mathematics 2022-02-08 Nicolò De Ponti , Sara Farinelli

N. Fournier and A. Guillin obtained in their 2015 PTRF paper some bounds of the L^p-mean rate of convergence in Wasserstein distance of empirical distributions for a class of stationary mixing processes. In this paper, we propose to extend…

Probability · Mathematics 2026-05-08 Gilles Pagès , Fabien Panloup

We study the perturbation of a measure $\mu \in \mathscr{P}(\mathbb{R})$ consisting in superposing two copies of $\mu$, each slightly shifted by a small distance $\pm h$. The difference between $\mu$ and its perturbation is measured with a…

Optimization and Control · Mathematics 2026-03-03 Averil Aussedat
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