Latest Articles for Graph Theory

Introducing MAGE: an innovative approach to explain Graph Neural Networks in chemistry.

This article explores the relationship between magnitude homology and path homology in directed graphs.

A new approach enhances querying in graph databases using ontologies.

Discover how random hyperbolic graphs represent real-world networks effectively.

Analyzing the significance of graph Laplacians in connectivity and structure.

This study presents methods to recover magnitude-symmetric matrices based on principal minors.

A look into triply efficient shadow tomography for quantum systems.

A fresh approach to keeping sensitive graph data safe online.

A new model for predicting links in dynamic graphs with clear explanations.

A look into how random graphs reveal growth patterns and properties.

A look at quasikernels and their significance in directed graphs.

A study on achieving balance in pathfinding based on diverse preferences.

A new method improves communication in graph data processing.

New methods improve efficiency for identifying dense subgraphs in large datasets.

Exploring order-preserving functions and their significance in semigroups.

A look into how parking functions model car parking and avoid patterns.

A new algorithm enhances sampling efficiency in tree-based Bayesian models.

A look into reflexive graphs and their applications through lenses.

A look into the properties and challenges of well-covered graphs.

A look into matchings, their types, and practical applications.

An overview of weighted oriented graphs and their significance in algebra.

Examining fairness in clustering methods for efficient data grouping.

Explore the relationships between matroids and quivers in mathematics.

A look into how networks form through exponential random graphs.

Exploring advanced methods for effective graph data analysis.

New model improves long-range information flow in graph data.

This study examines the complexities of the -Coloring problem in graphs.

Examining the links between matroids and Koszul algebras with real-world applications.

A new method for identifying key influencers in hypergraphs shows promising results.

Researchers develop a model to improve graph learning using data from various sources.

Examining key concepts of independent sets and hitting sets across various graphs.

Research develops methods for better understanding complex graph relationships.

This article examines the challenging nature of subtraction games in graph theory.

A detailed look at the Ising model, its interactions, and phase transitions.

Explore the connection between planar graphs and Maximal Mumford curves.

This article explores the challenges of graph coloring and minimal obstructions.

A framework to improve continual learning with graph-structured data.

A new framework improves predictions for unseen entities in knowledge graphs.

New method improves GNN stability across varied data situations.

A look at vertex cover, set cover, and hitting set problems in graph theory.