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We consider spectral methods that uncover hidden structures in directed networks. We establish and exploit connections between node reordering via (a) minimizing an objective function and (b) maximizing the likelihood of a random graph…

Social and Information Networks · Computer Science 2021-10-12 Xue Gong , Desmond John Higham , Konstantinos Zygalakis

The Laplace-Beltrami operator in the curved M\"obius strip is investigated in the limit when the width of the strip tends to zero. By establishing a norm-resolvent convergence, it is shown that spectral properties of the operator are…

Mathematical Physics · Physics 2022-08-22 Tomáš Kalvoda , David Krejcirik , Katerina Zahradova

This paper is concerned with the controllability problem of a connected threshold graph following the Laplacian dynamics. An algorithm is proposed to generate a spanning set of orthogonal Laplacian eigenvectors of the graph from a…

Optimization and Control · Mathematics 2018-06-14 Shun-Pin Hsu

In a paper by Nishikawa and Motter, a quantity called the normalized spread of the Laplacian eigenvalues is used to measure the synchronizability of certain network dynamics. Through simulations, and without theoretical validation, it is…

Optimization and Control · Mathematics 2026-01-09 Susie Lu , John Urschel , Ji Liu

We study the eigenvalues of a Laplace-Beltrami operator defined on the set of the symmetric polynomials, where the eigenvalues are expressed in terms of partitions of integers. By assigning partitions with the restricted uniform measure,…

Probability · Mathematics 2020-11-19 Tiefeng Jiang , Ke Wang

Laplacian operators on finite compact metric graphs are considered under the assumption that matching conditions at graph vertices are of $\delta$ and $\delta'$ types. An infinite series of trace formulae is obtained which link together two…

Spectral Theory · Mathematics 2014-11-06 Yulia Ershova , Irina I. Karpenko , Alexander V. Kiselev

We recover the Riemannian gradient of a given function defined on interior points of a Riemannian submanifold in the Euclidean space based on a sample of function evaluations at points in the submanifold. This approach is based on the…

Machine Learning · Computer Science 2023-06-06 Alvaro Almeida Gomez , Antônio J. Silva Neto , Jorge P. Zubelli

We investigate the behaviour of the regularized determinant of the Laplace-Beltrami operator on compact hyperbolic surfaces when the genus goes to infinity. We show that for all popular models of random surfaces, with high probability as…

Spectral Theory · Mathematics 2023-12-19 Frédéric Naud

We first develop a general framework for Laplace operators defined in terms of the combinatorial structure of a simplicial complex. This includes, among others, the graph Laplacian, the combinatorial Laplacian on simplicial complexes, the…

Algebraic Topology · Mathematics 2011-11-09 Danijela Horak , Jürgen Jost

We consider optimal control problems of elliptic PDEs on hypersurfaces in 2- or 3-dimensional Euclidean space. The leading part of the PDE is given by the Laplace-Beltrami operator, which is discretized by finite elements on a polyhedral…

Optimization and Control · Mathematics 2011-01-10 Michael Hinze , Morten Vierling

The eigenfunctions of the Laplacian are a natural basis of functions for many tasks in computational mathematics. On the circle and sphere, the eigenfunctions are given by complex periodic exponentials and spherical harmonics, respectively,…

Numerical Analysis · Mathematics 2026-05-22 Paul G. Beckman , Samuel F. Potter , Michael O'Neil

We consider the Laplace-Beltrami operator in tubular neighbourhoods of curves on two-dimensional Riemannian manifolds, subject to non-Hermitian parity and time preserving boundary conditions. We are interested in the interplay between the…

Mathematical Physics · Physics 2015-05-18 David Krejcirik , Petr Siegl

Adaptive bandwidth selection is a fundamental challenge in nonparametric regression. This paper introduces a new bandwidth selection procedure inspired by the optimality criteria for $\ell_0$-penalized regression. Although similar in spirit…

Machine Learning · Statistics 2025-05-21 Sabyasachi Chatterjee , Subhajit Goswami , Soumendu Sundar Mukherjee

Graphs are fundamental mathematical structures used in various fields to represent data, signals and processes. In this paper, we propose a novel framework for learning/estimating graphs from data. The proposed framework includes (i)…

Machine Learning · Computer Science 2017-07-07 Hilmi E. Egilmez , Eduardo Pavez , Antonio Ortega

We give a deterministic $\tilde{O}(\log n)$-space algorithm for approximately solving linear systems given by Laplacians of undirected graphs, and consequently also approximating hitting times, commute times, and escape probabilities for…

Computational Complexity · Computer Science 2017-08-17 Jack Murtagh , Omer Reingold , Aaron Sidford , Salil Vadhan

We investigate a variational method for ill-posed problems, named $\texttt{graphLa+}\Psi$, which embeds a graph Laplacian operator in the regularization term. The novelty of this method lies in constructing the graph Laplacian based on a…

Numerical Analysis · Mathematics 2024-10-22 Davide Bianchi , Davide Evangelista , Stefano Aleotti , Marco Donatelli , Elena Loli Piccolomini , Wenbin Li

A practical solution for the mathematical problem of functional calculus with Laplace-Beltrami operator on surfaces with axial symmetry is found. A quantitative analysis of the spectrum is presented.

Mathematical Physics · Physics 2009-10-31 E. Prodan

We estimate on a compact interval densities with isolated irregularities, such as discontinuities or discontinuities in some derivatives. From independent and identically distributed observations we construct a kernel estimator with…

Statistics Theory · Mathematics 2024-07-16 Céline Duval , Émeline Schmisser

The fractional Laplacian $(-\Delta)^{\alpha/2}$ is the prototypical non-local elliptic operator. While analytical theory has been advanced and understood for some time, there remain many open problems in the numerical analysis of the…

Numerical Analysis · Mathematics 2016-11-02 Yanghong Huang , Adam Oberman

We study a semi-supervised learning method based on the similarity graph and RegularizedLaplacian. We give convenient optimization formulation of the Regularized Laplacian method and establishits various properties. In particular, we show…

Machine Learning · Computer Science 2015-08-21 Konstantin Avrachenkov , Pavel Chebotarev , Alexey Mishenin