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Gaussian Processes (GPs) are a versatile method that enables different approaches towards learning for dynamics and control. Gaussianity assumptions appear in two dimensions in GPs: The positive semi-definite kernel of the underlying…

Machine Learning · Statistics 2024-09-13 T. Faulwasser , O. Molodchyk

We tackle the extension to the vector-valued case of consistency results for Stepwise Uncertainty Reduction sequential experimental design strategies established in [Bect et al., A supermartingale approach to Gaussian process based…

Statistics Theory · Mathematics 2023-10-12 Philip Stange , David Ginsbourger

In this work we consider regularized Wasserstein barycenters (average in Wasserstein distance) in Fourier basis. We prove that random Fourier parameters of the barycenter converge to some Gaussian random vector by distribution. The…

Statistics Theory · Mathematics 2021-09-21 Nazar Buzun

The envelope of an elliptical Gaussian complex vector, or equivalently, the amplitude or norm of a bivariate normal random vector has application in many weather and signal processing contexts. We explicitly characterize its distribution in…

Statistics Theory · Mathematics 2026-02-03 Sattwik Ghosal , Ranjan Maitra

We study distributions of random vectors whose components are second order polynomials in Gaussian random variables. Assuming that the law of such a vector is not absolutely continuous with respect to Lebesgue measure, we derive some…

Probability · Mathematics 2013-05-28 Vladimir I. Bogachev , Egor D. Kosov , Ivan Nourdin , Guillaume Poly

We consider the nodal length $L(\lambda)$ of the restriction to a ball of radius $r_\lambda$ of a {\it Gaussian pullback monochromatic random wave} of parameter $\lambda>0$ associated with a Riemann surface $(\mathcal M,g)$ without…

Probability · Mathematics 2020-05-15 Gauthier Dierickx , Ivan Nourdin , Giovanni Peccati , Maurizia Rossi

We derive a Gaussian Central Limit Theorem for the sample quantiles based on locally dependent random variables with explicit convergence rate. Our approach is based on converting the problem to a sum of indicator random variables, applying…

Probability · Mathematics 2025-03-05 Partha S. Dey , Grigory Terlov

We consider diffraction at random point scatterers on general discrete point sets in $\R^\nu$, restricted to a finite volume. We allow for random amplitudes and random dislocations of the scatterers. We investigate the speed of convergence…

Mathematical Physics · Physics 2007-05-23 C. Kuelske

We study the problem of measurement-induced decoherence using the phase-space approach employing the Gaussian-smoothed Wigner distribution function. Our investigation is based on the notion that measurement-induced decoherence is…

Quantum Physics · Physics 2009-11-10 Yong-Jin Chun , Hai-Woong Lee

The velocity of a passive particle in a one-dimensional wave field is shown to converge in law to a Wiener process, in the limit of a dense wave spectrum with independent complex amplitudes, where the random phases distribution is invariant…

Mathematical Physics · Physics 2012-07-12 Yves Elskens

There is a result of Diaconis and Freedman which says that, in a limiting sense, for large collections of high-dimensional data most one-dimensional projections of the data are approximately Gaussian. This paper gives quantitative versions…

Probability · Mathematics 2010-05-18 Elizabeth Meckes

To quantify the dependence between two random vectors of possibly different dimensions, we propose to rely on the properties of the 2-Wasserstein distance. We first propose two coefficients that are based on the Wasserstein distance between…

Statistics Theory · Mathematics 2021-10-19 Gilles Mordant , Johan Segers

We establish a strong law of large numbers and a central limit theorem in the Bures-Wasserstein space of covariance operators -- or equivalently centred Gaussian measures -- over a general separable Hilbert space. Specifically, we show that…

Probability · Mathematics 2024-11-05 Leonardo V. Santoro , Victor M. Panaretos

It is shown that the topologies and nestings of the zero and nodal sets of random (Gaussian) band limited functions have universal laws of distribution. Qualitative features of the supports of these distributions are determined. In…

Probability · Mathematics 2018-05-24 Peter Sarnak , Igor Wigman

It is shown that the topologies and nestings of the zero and nodal sets of random (Gaussian) band limited functions have universal laws of distribution. Qualitative features of the supports of these distributions are determined. In…

Mathematical Physics · Physics 2014-11-25 Peter Sarnak , Igor Wigman

We present large deviations principles for the moments of the empirical spectral measure of Wigner matrices and empirical measure of $\beta$-ensembles in three cases : the case of Wigner matrices without Gaussian tails, that is Wigner…

Probability · Mathematics 2016-05-13 Fanny Augeri

In this article the statistical properties of symmetrical random matrices whose elements are drawn from a q-parameterized non-extensive statistics power-law distribution are investigated. In the limit as q->1 the well known Gaussian…

Statistical Mechanics · Physics 2007-05-23 John Evans , Fredrick Michael

In this paper, we study random features manifested in components of energy eigenfunctions of quantum chaotic systems, given in the basis of unperturbed, integrable systems. Based on semiclassical analysis, particularly on Berry's…

Statistical Mechanics · Physics 2023-03-31 Jiaozi Wang , Wen-ge Wang

We study the nodal length of random toral Laplace eigenfunctions ("arithmetic random waves") restricted to decreasing domains ("shrinking balls"), all the way down to Planck scale. We find that, up to a natural scaling, for "generic"…

Mathematical Physics · Physics 2021-12-01 Jacques Benatar , Domenico Marinucci , Igor Wigman

We consider a system of diffusing particles on the real line in a quadratic external potential and with repulsive electrostatic interaction. The empirical measure process is known to converge weakly to a deterministic measure-valued process…

Probability · Mathematics 2010-03-23 Martin Bender