Latest Articles for Graph Theory

Discover the links between bipartite graphs and algebra in a friendly way.

A look into the fascinating structure and properties of matroids.

A dive into the Dirac operator and its eigenvalues through perturbations.

An overview of stretch metrics in graph data storage without redundancy.

Exploring edge coloring techniques in split graphs and their unique properties.

Discover the fascinating relationships between numbers through GCD-graphs.

Discover the quirky nature of antiregular graphs and their intriguing properties.

Learn how to optimize feature space from graph data.

Exploring the links between isogeny graphs and their level structures.

Using machine learning to study mutation-acyclic quivers with four points.

A look at independence numbers in unique graph structures.

A study on efficient vertex coloring techniques in specific graph structures.

Explore how rumors spread in social networks using the concept of burning numbers.

Mecoin helps retain memories while learning new information efficiently.

A look into the complexities of finding efficient paths in graphs.

An overview of higher-order trusses and their significance in analyzing complex networks.

Class Granularity helps organize knowledge graphs for better information retrieval.

Exploring zero forcing and its variant leaky forcing in graph theory.

Explore how spanners simplify connections in complex graphs.

Explore the dynamics of random graphs and their surprising connections.

Research advances in graph coloring using decision diagrams and fractional chromatic numbers.

Discover the complexities of coloring edges in graphs without clashes.

Discover the fascinating world of generalized Motzkin numbers and their colorful paths.

A look at how Graph Neural Networks tackle complex problems in optimization.

Graphs reveal relationships and connections in various systems.

A look into directed graphs, flag complexes, and their relationships.

ScaleNet improves graph analysis with innovative techniques for better node classification.

A simple guide to graphs and their role in connections.

Learn how regularization boosts the stability of Graph Neural Networks.

G-SPARC offers solutions for cold-start nodes in graph learning.

Graph neural networks help uncover patterns in quiver mutation for deeper mathematical insights.

Exploring relationships in groups through the concept of power graphs.

Explore the unique structures and significance of Bratteli diagrams in mathematical study.

A look into interval orders and how relationships can be organized.

New methods enhance GNNs using unique identifiers for better graph distinction.

This article examines how connection weights evolve over time in graphs.

Exploring interactions in multispin systems and their implications.

DuSEGO improves GNNs by addressing over-smoothing and gradient issues.

Exploring the relationship between infinite rings and their unique commuting graphs.

Learn how quantum computing tackles the weighted k problem using innovative techniques.