Latest Articles for Graph Theory

This study introduces a new method for positional encodings in directed graphs.

Introducing CNES for efficient link prediction in changing networks.

Research focuses on optimizing photonic graph states for quantum technologies.

Exploring how properties of random graphs affect their structure and connectivity.

A study on the properties and classifications of tetravalent independent-cycle type graphs.

New method enhances Graph Neural Network training efficiency and accuracy.

Examine advanced methods for finding shortest paths in Monge directed acyclic graphs.

RUM neural networks leverage random walks and memory for enhanced graph processing.

An examination of theories that lack the existence axiom and their implications.

Exploring methods and algorithms for finding paths in weighted graphs.

A new method for detecting anomalies in temporal knowledge graphs.

Exploring the relationship between quasi-transitive graphs and planar Cayley graphs.

Exploring new connections between biwords and Monge matrices through visual tools.

A look at systoles and their calculation on combinatorial surfaces.

Learn the parallel methods for verifying and analyzing minimum spanning trees.

CGRL tackles challenges in GNNs, improving classification despite popularity bias and noise.

A new method enhances graph clustering accuracy and efficiency.

A new method uses graph neural networks to improve graph coloring efficiency.

Discover how Graph Convolutional Networks analyze complex data in various fields.

Exploring the link between derangement graphs and orthogonal Latin squares.

This article discusses the importance of regular grammars in graph structures.

An exploration of chip-firing games in directed and undirected graphs.

A look into the distribution and importance of polynomial zeros.

A look at how Graph Neural Networks operate and their significance.

Explore game strategies and graph variations in Dots and Boxes.

Innovative techniques to analyze complex relationships in large graphs.

A look into how links are classified using local moves and invariants.

Exploring how inversion and treewidth impact graph analysis and properties.

Introducing PSNE, a method to improve network embeddings efficiently and effectively.

Examining the nature and probabilities of deficient sets in groupoids.

This article explores free groups, automorphisms, and cogrowth in group theory.

This article explores the significance of matchings in random graphs and their applications.

A novel approach to enhance understanding of GNN predictions through causal relationships.

A new framework enhances GNNs for better combinatorial optimization solutions.

Learn how subgraph queries enhance graph analysis and data predictions.

A fresh approach to visualize complex networks effectively.

Exploring the challenges and solutions for finding paths in graphs.

A deep dive into elliptic curves and the significance of Hessian transformations.

Discover the role of digraphs in relationships and mathematical structures.

REST improves prediction of missing connections in evolving knowledge graphs.