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This paper proposes a novel approach to the statistical characterization of non-central complex Gaussian quadratic forms (CGQFs). Its key strategy is the generation of an auxiliary random variable (RV) that converges in distribution to the…

Information Theory · Computer Science 2018-06-18 Pablo Ramírez-Espinosa , Laureano Moreno-Pozas , José F. Paris , José A. Cortés , Eduardo Martos-Naya

This manuscript considers the problem of learning a random Gaussian network function using a fully connected network with frozen intermediate layers and trainable readout layer. This problem can be seen as a natural generalization of the…

Machine Learning · Statistics 2023-02-02 Dominik Schröder , Hugo Cui , Daniil Dmitriev , Bruno Loureiro

We study the asymptotic laws for the number, Betti numbers, and isotopy classes of connected components of zero sets of real Gaussian random fields, where the random zero sets almost surely consist of submanifolds of codimension greater…

Probability · Mathematics 2023-09-26 Zhengjiang Lin

Fourier feature approximations have been successfully applied in the literature for scalable Gaussian Process (GP) regression. In particular, Quadrature Fourier Features (QFF) derived from Gaussian quadrature rules have gained popularity in…

Machine Learning · Statistics 2023-10-24 Kevin Li , Max Balakirsky , Simon Mak

A major effort in modern high-dimensional statistics has been devoted to the analysis of linear predictors trained on nonlinear feature embeddings via empirical risk minimization (ERM). Gaussian equivalence theory (GET) has emerged as a…

Statistics Theory · Mathematics 2025-12-04 Garrett G. Wen , Hong Hu , Yue M. Lu , Zhou Fan , Theodor Misiakiewicz

Physical reasons suggested in \cite{Ha-Ha} for the \emph{Quantum Gravity Problem} lead us to study \emph{type-changing metrics} on a manifold. The most interesting cases are \emph{Transverse Riemann-Lorentz Manifolds}. Here we study the…

Differential Geometry · Mathematics 2015-06-26 E. Aguirre , V. Fernández , J. Lafuente

Given a closed orientable surface (\Sigma) of genus at least two, we establish an affine isomorphism between the convex compact set of isotopy-invariant topological measures on (\Sigma) and the convex compact set of additive functions on…

General Topology · Mathematics 2009-03-17 Frol Zapolsky

We develop, simulate and extend an initial proposition by Chaves et al. concerning a random incompressible vector field able to reproduce key ingredients of three-dimensional turbulence in both space and time. In this article, we focus on…

A sum of lognormal random variables (RVs) appears in many problems of science and engineering. For example, it is invloved in computing the distribution of recevied signal and interference powers for radio channels subject to lognormal…

Signal Processing · Electrical Eng. & Systems 2024-05-16 Fredrik Berggren

We test the hypothesis that the microscopic temporal structure of near-field turbulence downstream of a sudden contraction contains geometry-identifiable information pertaining to the shape of the upstream obstruction. We measure a set of…

Fluid Dynamics · Physics 2024-12-17 Mukesh Karunanethy , Raghunathan Rengaswamy , Mahesh V Panchagnula

We study the random geometry approach to the $T\bar{T}$ deformation of 2d conformal field theory developed by Cardy and discuss its realization in a gravity dual. In this representation, the gravity dual of the $T\bar{T}$ deformation…

High Energy Physics - Theory · Physics 2020-11-24 Shinji Hirano , Masaki Shigemori

In this paper we continue the programme of topologically twisting N=2 theories in D=4, focusing on the coupling of vector multiplets to N=2 supergravity. We show that in the minimal case, namely when the special geometry prepotential F(X)…

High Energy Physics - Theory · Physics 2010-11-02 Damiano Anselmi , Pietro Fre'

We study "random surfaces," which are random real (or integer) valued functions on Z^d. The laws are determined by convex, nearest neighbor, difference potentials that are invariant under translation by a full-rank sublattice L of Z^d; they…

Probability · Mathematics 2007-05-23 Scott Sheffield

The scaling properties of quantum gravity are discussed by employing a class of proper-time regulators in the functional flow equation for the conformal factor within the formalism of the background field method. Renormalization group…

High Energy Physics - Theory · Physics 2013-12-10 Alfio Bonanno , Filippo Guarnieri

We investigate joint spectral characteristics of a family of matrices $\mathcal F $, associated with products in the semigroup generated by $\mathcal F$. In the literature, extremal measures such as the well-known joint spectral radius and…

Dynamical Systems · Mathematics 2026-04-27 Francesco Paolo Maiale , Anastasiia Trofimova , Nicola Guglielmi

The dynamics of the torsion field is analyzed in the framework of the Covariant Canonical Gauge Theory of Gravity (CCGG), a De~Donder-Weyl Hamiltonian formulation of gauge gravity. The action is quadratic in both, the torsion and the…

General Relativity and Quantum Cosmology · Physics 2024-05-29 Vladimir Denk , David Vasak , Johannes Kirsch

This paper deals with a new class of random flights $\underline{\bf X}_d(t),t>0,$ defined in the real space $\mathbb{R}^d, d\geq 2,$ characterized by non-uniform probability distributions on the multidimensional sphere. These random motions…

Probability · Mathematics 2015-05-30 Alessandro De Gregorio

We introduce a theoretical framework for differentiable surface evolution that allows discrete topology changes through the use of topological derivatives for variational optimization of image functionals. While prior methods for inverse…

Computer Vision and Pattern Recognition · Computer Science 2023-08-22 Ishit Mehta , Manmohan Chandraker , Ravi Ramamoorthi

We show that the Ginsparg-Wilson (GW) relation can play an important role to define chiral structures in {\it finite} noncommutative geometries. Employing GW relation, we can prove the index theorem and construct topological invariants even…

High Energy Physics - Theory · Physics 2009-11-07 Hajime Aoki , Satoshi Iso , Keiichi Nagao

We investigate the low-dimensional structure of deterministic transformations between random variables, i.e., transport maps between probability measures. In the context of statistics and machine learning, these transformations can be used…

Methodology · Statistics 2018-12-18 Alessio Spantini , Daniele Bigoni , Youssef Marzouk