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We use a Harnack-type inequality on exit times and spectral bounds to characterize upper bounds of the heat kernel associated with any regular Dirichlet form without killing part, where the scale function may vary with position. We further…

Probability · Mathematics 2025-09-03 Aobo Chen , Zhenyu Yu

In this article we study the Quillen norm on the determinant line bundle associated with a family of complex curves with cusps, which admit singular fibers. More precisely, we fix a family of complex curves $\pi : X \to S$, which admit at…

Differential Geometry · Mathematics 2022-07-08 Siarhei Finski

The goal of this work is to shed light on the remarkable phenomenon of transition to linearity of certain neural networks as their width approaches infinity. We show that the transition to linearity of the model and, equivalently, constancy…

Machine Learning · Computer Science 2021-02-23 Chaoyue Liu , Libin Zhu , Mikhail Belkin

This paper explores a new perspective on the universality of the vertical lift in tangent categories by presenting a categorification of the dimension of smooth manifolds. The universality of the vertical lift is a key part of the axioms of…

Category Theory · Mathematics 2026-02-18 Florian Schwarz

We consider a multivariate version of the so-called Lancaster problem of characterizing canonical correlation coefficients of symmetric bivariate distributions with identical marginals and orthogonal polynomial expansions. The marginal…

Probability · Mathematics 2013-03-21 Robert C. Griffiths , Dario Spanò

We show that near a point where the equilibrium density of eigenvalues of a matrix model behaves like y ~ x^{p/q}, the correlation functions of a random matrix, are, to leading order in the appropriate scaling, given by determinants of the…

Mathematical Physics · Physics 2009-09-08 Michel Bergere , Bertrand Eynard

This paper studies strongly local symmetric Dirichlet forms on general measure spaces. The underlying space is equipped with the intrinsic metric induced by the Dirichlet form, with respect to which the metric measure space does not…

Probability · Mathematics 2016-10-24 Shuwen Lou

Runge's method is a tool to figure out integral points on curves effectively in terms of height. This method has been generalised to varieties of any dimension, unfortunately its conditions of application are often too restrictive. In this…

Number Theory · Mathematics 2019-03-06 Samuel Le Fourn

We analyse the local geometric structure of self-similar sets with open set condition through the study of the properties of a distinguished family of spherical neighbourhoods, the typical balls. We quantify the complexity of the local…

Dynamical Systems · Mathematics 2023-08-16 Manuel Morán , Marta LLorente , María Eugenia

The problem of establishing out-of-sample bounds for the values of an unkonwn ground-truth function is considered. Kernels and their associated Hilbert spaces are the main formalism employed herein along with an observational model where…

Machine Learning · Computer Science 2022-09-13 Paul Scharnhorst , Emilio T. Maddalena , Yuning Jiang , Colin N. Jones

A Hilbert space embedding for probability measures has recently been proposed, wherein any probability measure is represented as a mean element in a reproducing kernel Hilbert space (RKHS). Such an embedding has found applications in…

Machine Learning · Statistics 2010-03-04 Bharath K. Sriperumbudur , Kenji Fukumizu , Gert R. G. Lanckriet

Let $Q$ denote the space of signed measures on the Borel $\sigma$-algebra of a separable complete space $X$. We endow $Q$ with the norm $\|q\|=\sup|\int\phi dq|$, where the supremum is taken over all Lipschitz with constant 1 functions…

Functional Analysis · Mathematics 2007-09-20 Andriy Yurachkivsky

We consider an abstract compact orientable Cauchy-Riemann manifold endowed with a Cauchy-Riemann complex line bundle. We assume that the manifold satisfies condition Y(q) everywhere. In this paper we obtain a scaling upper-bound for the…

Complex Variables · Mathematics 2012-05-22 Chin-Yu Hsiao , George Marinescu

We study a two-dimensional family of probability measures on infinite Gelfand-Tsetlin schemes induced by a distinguished family of extreme characters of the infinite-dimensional unitary group. These measures are unitary group analogs of the…

Representation Theory · Mathematics 2011-03-08 Alexei Borodin , Jeffrey Kuan

Bleher and Kuijlaars, and Daems and Kuijlaars showed that the correlation functions of the eigenvalues of a random matrix from unitary ensemble with external source can be expressed in terms of the Christoffel-Darboux kernel for multiple…

Complex Variables · Mathematics 2008-09-24 Jinho Baik

There are currently two parameterizations used to derive fixed kernels corresponding to infinite width neural networks, the NTK (Neural Tangent Kernel) parameterization and the naive standard parameterization. However, the extrapolation of…

Machine Learning · Computer Science 2020-04-21 Jascha Sohl-Dickstein , Roman Novak , Samuel S. Schoenholz , Jaehoon Lee

Recently, it was proved that group equivariance emerges in ensembles of neural networks as the result of full augmentation in the limit of infinitely wide neural networks (neural tangent kernel limit). In this paper, we extend this result…

Machine Learning · Computer Science 2025-12-19 Oskar Nordenfors , Axel Flinth

We study multivariable Christoffel-Darboux kernels, which may be viewed as reproducing kernels for antisymmetric orthogonal polynomials, and also as correlation functions for products of characteristic polynomials of random Hermitian…

Classical Analysis and ODEs · Mathematics 2008-04-24 Hjalmar Rosengren

We study the density estimation problem with observations generated by certain dynamical systems that admit a unique underlying invariant Lebesgue density. Observations drawn from dynamical systems are not independent and moreover, usual…

Machine Learning · Statistics 2016-07-14 Hanyuan Hang , Ingo Steinwart , Yunlong Feng , Johan A. K. Suykens

This paper investigates the relationship between various measure-theoretic properties of U-statistics with fixed sample size $N$ and the same properties of their kernels. Specifically, the random variables are replaced with elements in some…

Classical Analysis and ODEs · Mathematics 2015-07-15 Irina Navrotskaya