Let G be a graph, A(G) be the adjacency matrix of G, and λ(G) the least eigenvalue of A(G). Information is given about the following three quantities: $\lambda_R(G ...

This project provides a simple implementation of a weighted undirected graph using adjacency linked lists, designed to efficiently handle sparse graphs. It includes several classic graph algorithms ...

Abstract: Computing the product of the (binary) adjacency matrix of a large graph with a real-valued vector is an important operation that lies at the heart of various graph analysis tasks, such as ...

Abstract: Graph clustering is a core technique for network analysis problems, e.g., community detection. This work puts forth a node clustering approach for largely incomplete adjacency graphs. Under ...

This repository is dedicated to learning and practicing the Graph data structure using an adjacency list implementation in Java. It serves as a personal study project to understand graph concepts, ...

Carpathian Journal of Mathematics, Vol. 39, No. 1 (2023), pp. 213-230 (18 pages) The normalized distance Laplacian matrix of a connected graph G, denoted by D𝓛(G), is defined by D𝓛(G) = ...