Latest Articles for Network Analysis

Learn about Markov chains and their vital role in various fields.

Insights into Bitcoin's structure, user behavior, and network changes over time.

A look into the complexities of edge coloring with even color requirements.

This research enhances estimation methods for understanding complex networks.

A look into indirect methods for understanding social networks.

A new framework improves robustness of Graph Contrastive Learning against structural attacks.

New methods help identify time scales in complex networks.

Exploring the balance of graph colorings and their implications in mathematics.

This study focuses on identifying paths in networks of disks.

A deep dive into how temporal networks track interactions over time.

Learn how hypergraphs help in understanding complex systems and interactions.

Ordinal methods reveal insights into complex network behaviors and interactions.

Research tackles the Maximum Weighted Digraph Partition problem for optimal graph division.

Learn how NSBM helps analyze unlabeled networks and detect communities effectively.

Discover methods for efficient testing of graph properties.

This article explores LCL problems and their complexities in tree structures.

A novel model generates realistic synthetic graphs for better network analysis.

Introducing a method to improve node clustering in complex networks.

A fresh approach improves solutions for complex graph challenges.

S2PGNN improves the adaptation of GNNs to labeled data.

A look at modularity and its role in understanding community structures in networks.

Min-diameter measures the longest shortest path in directed graphs, revealing connectivity.

Exploring new methods for efficient distance queries in graph algorithms using algebraic techniques.

A look into graphs, their structures, and important concepts.

A new algorithm improves graph cuts for efficient data clustering.

This study looks at cliques and their impact on graph properties.

A new approach to understanding graph-structured data and node relationships.

R enyi entropy helps quantify diversity in ecosystems and other complex systems.

A method for improving graph partitioning by using buffer nodes.

This study examines how changes in cycles affect information mixing speed.

This study discusses eigenvectors, data analysis methods, and challenges with small eigengaps.

New method reduces memory usage in managing temporal graphs.

A study on how spectral independence affects system stability and mixing time.

Exploring the relationship between eigenvalues and independence complexes in graph theory.

A new method for counting graphlets in changing networks.

A look at segment and line cover numbers in graph representation.

Addressing over-squashing can improve the performance of Graph Neural Networks.

A new method for efficiently finding maximum 2-packing sets in graphs.

New algorithms improve solutions for the Maximum Bimodal Subgraph problem.

Introducing a model that enhances network analysis through improved representation techniques.