Spectral analysis connects graph structure to the eigenvalues and eigenvectors of associated matrices. Much of spectral graph theory descends directly from spectral geometry, the study of differentiable manifolds through the spectra of associated differential operators.
May 23, 2019
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May 23, 2019 · In this paper, we show how methods used to study densities of states in condensed matter physics [49] can be used to study spectral densities in ...
Beyond providing visually compelling fingerprints of graphs, we show how the estimation of spectral densities facilitates the computation of many common ...
Network density is the ratio of the number of actual links to the possible or potential links of a network.
I Weyl's Law connects the geometric properties of a manifold with the asymptotic spectral distribution of Laplace-Beltrami operator.
Feb 17, 2022 · Mat2Spec is an exemplar framework for predicting spectral properties of materials via strategically incorporated machine learning techniques.
Sep 27, 2024 · We explore the neural network density of states - the number of network parameter configurations that produce a given loss value - and analyze how it depends ...
This repository contains the experiments of the Network Density of States by Kun Dong, Austin Benson, David Bindel. This paper will be appearing at KDD 2019 ...
Beyond providing visually compelling fingerprints of graphs, this paper shows how the estimation of spectral densities facilitates the computation of many ...
Oct 27, 2024 · In this paper we introduce the density of states as a tool for studying the space of all possible network partitions. We demonstrate how to use ...