Latest Articles for Network Analysis

Learn how community detection shapes networks and enhances various fields.

New strategies enhance GNN performance in multi-label node classification tasks.

Discover innovative methods for sampling signals using graph theory.

Exploring the relationships between graphons and their unique traits.

A method for better predictions in shifting data environments.

Explore how POGAT enhances the analysis of complex graph structures.

Examining the Hall ratio and fractional chromatic number in graph theory.

Exploring the relationship between graph distance metrics and shape.

Explore how different connections shape networks using causal inference.

A concise look at community detection within networks and its applications.

Discover how identifying key influencers can impact marketing and public health.

A look into how digraphs help analyze complex systems.

This article examines distances in Kronecker products of distance regular graphs.

New GCN model improves analysis of complex relationships in graph data.

A new model improves our grasp of complex networks and their interactions.

Researchers enhance GNNs to improve predictions in complex data relationships.

Explore how community recovery shapes group dynamics across multiple networks.

Discover how math helps us understand friendships and social interactions.

Inceptive Graph Neural Networks bridge the gap between homophily and heterophily for better data representation.

Learn how to spread ideas through strategic influence in social networks.

A fresh look at community detection using semi-supervised methods in networks.

Discover how random graphs shape our understanding of connections and rigidity.

Discover how random walks work in graphs and their real-life applications.

Explore how weighted graphs reflect relationships and behaviors in mathematics.

Using advanced models to analyze international trade relationships and their hidden structures.

Explore the fascinating world of games shaped by time and strategy.

Discover when Graph Attention Networks shine and when simpler methods prevail.

Discover how edge filtration enhances graph neural networks for better data representation.

Silencer framework enhances community detection amid noise for accurate network analysis.

Explore how Network Stochastic Differential Equations enhance our grasp of interconnected systems.

Mathematicians investigate a challenging conjecture about directed graphs and their connections.

Learn how local ultrametric approximations make graph distance calculations easier.