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We study a class of semialgebraic convex bodies called discotopes. These are instances of zonoids, objects of interest in real algebraic geometry and random geometry. We focus on the face structure and on the boundary hypersurface of…

Algebraic Geometry · Mathematics 2025-06-02 Fulvio Gesmundo , Chiara Meroni

This paper presents new results allowing an unknown non-Gaussian positive matrix-valued random field to be identified through a stochastic elliptic boundary value problem, solving a statistical inverse problem. A new general class of…

Statistics Theory · Mathematics 2019-02-20 Anthony Nouy , Christian Soize

We study when a given Gaussian random variable on a given probability space $(\Omega, {\cal{F}}, P) $ is equal almost surely to $\beta_{1}$ where $\beta $ is a Brownian motion defined on the same (or possibly extended) probability space. As…

Probability · Mathematics 2009-08-24 Ciprian Tudor

We derive a Gaussian approximation result for the maximum of a sum of high-dimensional random vectors. Specifically, we establish conditions under which the distribution of the maximum is approximated by that of the maximum of a sum of the…

Statistics Theory · Mathematics 2018-01-24 Victor Chernozhukov , Denis Chetverikov , Kengo Kato

Let $X$ be a symmetric, isotropic random vector in $\mathbb{R}^m$ and let $X_1...,X_n$ be independent copies of $X$. We show that under mild assumptions on $\|X\|_2$ (a suitable thin-shell bound) and on the tail-decay of the marginals…

Functional Analysis · Mathematics 2022-07-13 Daniel Bartl , Shahar Mendelson

Let $X,X_1,X_2,\ldots$ be i.i.d. ${\mathbb{R}}^d$-valued real random vectors. Assume that ${\mathbf{E}X=0}$, $\operatorname {cov}X=\mathbb{C}$, $\mathbf{E}\Vert X\Vert^2=\sigma ^2$ and that $X$ is not concentrated in a proper subspace of…

Probability · Mathematics 2014-01-15 Friedrich Götze , Andrei Yu. Zaitsev

The long-standing Gaussian product inequality (GPI) conjecture states that, for any centered $\mathbb{R}^n$-valued Gaussian random vector $(X_1, \dots, X_n)$ and any positive reals $\alpha_1, \dots, \alpha_n$, ${\bf…

Probability · Mathematics 2023-08-29 Qian-Qian Zhou , Han Zhao , Ze-Chun Hu , Renming Song

We study the geometry of centrally-symmetric random polytopes, generated by $N$ independent copies of a random vector $X$ taking values in $\mathbb{R}^n$. We show that under minimal assumptions on $X$, for $N \gtrsim n$ and with high…

Probability · Mathematics 2019-07-18 Olivier Guédon , Felix Krahmer , Christian Kümmerle , Shahar Mendelson , Holger Rauhut

We consider multivariate centered Gaussian models for the random variable $Z=(Z_1,\ldots, Z_p)$, invariant under the action of a subgroup of the group of permutations on $\{1,\ldots, p\}$. Using the representation theory of the symmetric…

Statistics Theory · Mathematics 2022-05-17 Piotr Graczyk , Hideyuki Ishi , Bartosz Kołodziejek , Hélène Massam

Structure formation in our Universe creates non-Gaussian random fields that will soon be observed over almost the entire sky by the Euclid satellite, the Vera-Rubin observatory, and the Square Kilometre Array. An unsolved problem is how to…

Cosmology and Nongalactic Astrophysics · Physics 2021-12-10 Joey R. Braspenning , Elena Sellentin

This paper considers the objective comparison of stochastic models to solve inverse problems, more specifically image restoration. Most often, model comparison is addressed in a supervised manner, that can be time-consuming and partly…

Computation · Statistics 2020-10-14 Benjamin Harroué , Jean-François Giovannelli , Marcelo Pereyra

A random vector whose norm and overlap (inner product with an independent copy) concentrates is shown to have random low-dimensional projections that are approximately random Gaussians. Conversely, asymptotically random Gaussian projections…

Probability · Mathematics 2025-12-23 Timothy L. H. Wee , Sekhar Tatikonda

We derive exact asymptotics of $$\mathbb{P}\left(\sup_{\mathbf{t}\in {\mathcal{A}}}X(\mathbf{t})>u\right),~ \text{as}~ u\to\infty,$$ for a centered Gaussian field $X(\mathbf{t}),~ \mathbf{t}\in \mathcal{A}\subset\mathbb{R}^n$, $n>1$ with…

Probability · Mathematics 2021-11-17 Long Bai , Krzysztof Debicki , Peng Liu

We obtain a tail bound for the least non-zero singular value of $A-z$ when $A$ is a random matrix and $z$ is an eigenvalue of $A$ in a neighbourhood of a given point $z_0$ in the bulk of the spectrum. The argument relies on a resolvent…

Probability · Mathematics 2024-04-22 Mohammed Osman

We develop a calculus based on zonoids - a special class of convex bodies - for the expectation of functionals related to a random submanifold $Z$ defined as the zero set of a smooth vector valued random field on a Riemannian manifold. We…

Probability · Mathematics 2023-03-23 Léo Mathis , Michele Stecconi

This paper studies polar sets of anisotropic Gaussian random fields, i.e. sets which a Gaussian random field does not hit almost surely. The main assumptions are that the eigenvalues of the covariance matrix are bounded from below and that…

Probability · Mathematics 2020-06-12 Jakob Söhl

Choose n random, independent points in R^d according to a fixed distribution. The convex hull of these points is a random polytope. In some cases, central limit theorems have been proven for the components of f-vectors of random polytopes…

Metric Geometry · Mathematics 2011-09-22 Sang Du , Mark Syvuk

The ellipsoid fitting conjecture of Saunderson, Chandrasekaran, Parrilo and Willsky considers the maximum number $n$ random Gaussian points in $\mathbb{R}^d$, such that with high probability, there exists an origin-symmetric ellipsoid…

Probability · Mathematics 2023-07-25 Madhur Tulsiani , June Wu

We consider the family of convex bodies obtained from an origin symmetric convex body $K$ by multiplication with diagonal matrices, by forming Minkowski sums of the transformed sets, and by taking limits in the Hausdorff metric. Support…

Metric Geometry · Mathematics 2019-09-10 Ilya Molchanov , Felix Nagel

We derive a Gaussian approximation result for the maximum of a sum of random vectors under $(2+\iota)$-th moments. Our main theorem is abstract and nonasymptotic, and can be applied to a variety of statistical learning problems. The proof…

Statistics Theory · Mathematics 2019-05-28 Qiang Sun