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We study stability and local minimizing properties of $L^p$- norms of Riemannian curvature tensor denoted by $\mathcal{R}_p$ by variational methods. We compute the Hessian of $\mathcal{R}_p$ at compact rank 1 symmetric spaces and prove that…

Differential Geometry · Mathematics 2018-03-20 Soma Maity

The consensus problem -- achieving agreement among a network of agents -- is a central theme in both theory and applications. Recently, this problem has been extended from Euclidean spaces to the space of probability measures, where the…

Optimization and Control · Mathematics 2025-10-01 Pilgyu Jung , Yoon Mo Jung

Let $\mu$ be a doubling measure in $\mathbb{R}^n$. We investigate quantitative relations between the rectifiability of $\mu$ and its distance to flat measures. More precisely, for $x$ in the support $\Sigma$ of $\mu$ and $r > 0$, we…

Classical Analysis and ODEs · Mathematics 2014-08-29 Jonas Azzam , Guy David , Tatiana Toro

This paper is a continuation of our accompanying paper [Talbi, Touzi and Zhang (2021)], where we characterized the mean field optimal stopping problem by an obstacle equation on the Wasserstein space of probability measures, provided that…

Probability · Mathematics 2022-11-18 Mehdi Talbi , Nizar Touzi , Jianfeng Zhang

This paper will introduce a family of sliced Wasserstein geodesics which are not standard Wasserstein geodesics, objects yet to be discovered in the literature. These objects exhibit how the geometric structure of the Sliced Wasserstein…

Probability · Mathematics 2024-07-11 John Seale Hopper

We study the geometric structure of weighted Einstein smooth metric measure spaces with weighted harmonic Weyl tensor. A complete local classification is provided, showing that either the underlying manifold is Einstein, or decomposes as a…

Differential Geometry · Mathematics 2023-05-16 Miguel Brozos-Vázquez , Diego Mojón-Álvarez

We prove that if $\Om \subseteq \R^2$ is bounded and $\R^2 \setminus \Om$ satisfies suitable structural assumptions (for example it has a countable number of connected components), then $W^{1,2}(\Om)$ is dense in $W^{1,p}(\Om)$ for every…

Analysis of PDEs · Mathematics 2007-05-23 Alessandro Giacomini , Paola Trebeschi

This report has several purposes. First, our report is written to investigate the reproducibility of the submitted paper On the regularization of Wasserstein GANs (2018). Second, among the experiments performed in the submitted paper, five…

Machine Learning · Computer Science 2017-12-19 Junghoon Seo , Taegyun Jeon

Uniformity testing and the more general identity testing are well studied problems in distributional property testing. Most previous work focuses on testing under $L_1$-distance. However, when the support is very large or even continuous,…

Machine Learning · Computer Science 2017-10-31 Shichuan Deng , Wenzheng Li , Xuan Wu

In this paper, we study the stability of the shadow, a projection of a measure onto the set of couplings with respect to the Wasserstein distance. The shadow was introduced by \citet{Eckstein_Nutz_2022} to analyze the stability of the…

Statistics Theory · Mathematics 2026-04-21 Jakwang Kim

We provide a short proof that the Wasserstein distance between the empirical measure of a n-sample and the estimated measure is of order n^-(1/d), if the measure has a lower and upper bounded density on the d-dimensional flat torus.

Statistics Theory · Mathematics 2021-01-21 Vincent Divol

This paper provides a study of problems related to Hardy spaces left by G.\,Weiss in \cite{We}. First, We will prove that the Hardy spaces $H^p(\mathbb{R}^n)$ can be characterized by a fixed Lipschitz function.

Functional Analysis · Mathematics 2022-06-30 ZhuoRan Hu

We study nonparametric density estimation problems where error is measured in the Wasserstein distance, a metric on probability distributions popular in many areas of statistics and machine learning. We give the first minimax-optimal rates…

Statistics Theory · Mathematics 2020-04-30 Jonathan Niles-Weed , Quentin Berthet

We build on recent work linking backward and forward W2-projections in convex order with the recently introduced metric extrapolation problem to derive new quantitative stability estimates for both problems.

Optimization and Control · Mathematics 2026-04-15 Jakwang Kim , Young-Heon Kim , Andrea Natale

We study the Wasserstein metric $W_p$, a notion of distance between two probability distributions, from the perspective of Fourier Analysis and discuss applications. In particular, we bound the Earth Mover Distance $W_1$ between the…

Classical Analysis and ODEs · Mathematics 2020-09-15 Stefan Steinerberger

We prove the claim in the title under mild conditions which are usually satisfied when trying to establish asymptotic normality. We assume strictly stationary and absolutely regular data.

Statistics Theory · Mathematics 2024-05-13 Marius Kroll

We define a metric in the space of positive finite positive measures that extends the 2-Wasserstein metric, i.e. its restriction to the set of probability measures is the 2-Wasserstein metric. We prove a dual and a dynamic formulation and…

Metric Geometry · Mathematics 2023-03-07 Hugo Leblanc , Thibaut Le Gouic , Jacques Liandrat , Magali Tournus

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

We prove an inequality on the Kantorovich-Rubinstein distance --which can be seen as a particular case of a Wasserstein metric-- between two solutions of the spatially homogeneous Boltzmann equation without angular cutoff, but with a…

Analysis of PDEs · Mathematics 2010-02-02 Nicolas Fournier , Clément Mouhot

In one of his recent papers \cite{ML1}, Moln\'ar showed that if $\mathcal{A}$ is a von Neumann algebra without $I_1, I_2$-type direct summands, then any function from the positive definite cone of $\mathcal{A}$ to the positive real numbers…

Operator Algebras · Mathematics 2023-07-17 Richárd Simon , Dániel Virosztek