Latest Articles for Network Analysis

Learn how to build graphs and achieve specific properties in a semi-random game.

A new method to analyze evolving labeled networks effectively.

Exploring how walks in graphs influence various fields of study.

Learn how graph coalescence helps model complex systems in various fields.

A new approach to estimate eigenvalues of large matrices efficiently.

Exploring the relationship between random arrangements and graph structures.

This study improves GNNs' ability to handle multi-node tasks using innovative labeling techniques.

GCNH improves learning from complex graph structures, tackling heterophily effectively.

Explore how advanced measures deepen insights into global trade relationships.

Examining new methods for understanding node embeddings and their significance.

This article examines a method for generating simple path graphs with limited hops.

Multiple GFT designs enhance signal analysis in directed graphs.

Insights into job flow and performance in queuing systems under heavy traffic.

A new approach enhances understanding of social networks through individual differences.

Graph Random Features offer faster and efficient calculations for graph kernels.

This article explores k-anonymity and its impact on network privacy.

New model GraphSANN tackles challenges in imbalanced node classification effectively.

A look into the role of betweenness centrality across various networks.

Explore the features and applications of directed graphs in various fields.

A new method to find overlapping groups in complex networks.

A comprehensive look at unitary addition Cayley graphs and their properties.

Exploring ways to enhance connections in directed graphs through various problems.

A deep dive into community robustness and its implications.

New insights into the performance and convergence of Graph Neural Networks.

EDGE offers a more efficient way to generate complex graphs.

Explore the Alon-Tarsi number and its significance in graph coloring and properties.

Blowback traffic poses challenges for researchers and can amplify attacks.

A look at the properties and applications of self-loop graphs in various fields.

Exploring the properties and configurations of doubly Eulerian graphs and their avoidance indices.

Exploring the dynamics of coalitions and their role in graph structures.

A look into saturation numbers in graphs and their applications.

This article discusses methods for assigning edge weights based on graph structure.

This study examines how hidden features in graphs can predict node outcomes.

A look into sparse graphs, degeneracy, and induced paths.

A method for creating temporal graphs with specific properties efficiently.

This research enhances node classification using label non-uniformity in graph neural networks.

A new tool for analyzing complex networks using graphlet analysis.

Study of VDFAP channels reveals key insights into molecular communication capacity.

This study investigates graphons under specific constraints related to edge and 2star densities.

DNND offers a fresh method for accurate dynamic modeling without embedding issues.