Spectral graph theory is the study of the eigenvalues and eigenvectors of matrices associated with graphs. In this tutorial, we will try to provide some intuition as to why these eigenvectors and ...

We give a survey of graph spectral techniques used in computer sciences. The survey consists of a description of particular topics from the theory of graph spectra independently of the areas of ...

The method leverages the graph Laplacian, a matrix that represents pairwise relationships between data points. The Laplacian matrix, defined as L=D−A (where A is the similarity matrix and D is the ...

CNN_Graph.pytorch This repository is an unofficial implement of the paper "Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering" in NIPS 2016 with PyTorch. It supports to ...

The α-spectral radius of G is the largest eigenvalue of Aα (G). For a graph with two pendant paths at a vertex or at two adjacent vertices, we prove results concerning the behavior of the α-spectral ...

Further, we propose a framework that integrates the dynamically captured spectra in the form of these learnable wavelets into spatial features for incorporating local and global interactions.

Children with Autism Spectrum Disorder (ASD) frequently exhibit comorbid anxiety, which contributes to impairment and requires treatment. Therefore, it is critical to investigate co-occurring autism ...