Latest Articles for Graph Theory

A novel method improves graph generation by considering node and edge attributes together.

This study examines privacy concerns in graph representation learning and edge reconstruction attacks.

An overview of MPNNs, their workings, and applications in various fields.

A new method enhances blind deconvolution in graph signals despite imperfect information.

New methods improve graph learning through non-discrete bandwidth masking techniques.

Discover how succinct data structures optimize chordal graphs for various applications.

A method to predict missing information in graph nodes using local structures.

This article presents a fresh view on the Four Color Theorem using R/G/B coloring and graph analysis.

A straightforward look at the Four Color Theorem and its importance.

This study improves GNN performance through effective graph explanations.

Explore how hypergraphs capture complex relationships in social networks and biology.

An overview of perfect matchings in graph theory and their significance.

Exploring how graphs can be distinguished through their spectral properties.

Learn about hypergraphs, their definitions, types, and important properties in graph theory.

A2GNN model enhances performance in adapting graph knowledge across different domains.

A new framework improves dynamic graph analysis, addressing key challenges in representation.

A new framework improves the clarity and scalability of graph visualizations.

This study presents methods for finding minimum weight feedback vertex sets in tournaments.

New findings shed light on coloring triangle-free graphs and Vizing's problem.

A look into the relationships within 2-level polytopes and their subsets.

HPLC enhances link prediction in graphs through landmark selection and clustering.

Introducing message detouring for improved graph cycle representation.

Examining the role of distance matrices in tree and bipartite graph analysis.

Explore the complexities of directed graphs with vertex weights and edge ideals.

This article examines how Transformers solve problems using stepwise inference and graph models.

A look into the unique properties of edge-ordered graphs and their restrictions.

Introducing a new model for predicting connections in various graph types.

New methods use graph theory to enhance structural controllability in switched systems.

A study on maintaining vertex covers and matchings in changing geometric environments.

A look into the Four Color Theorem and its significance in mathematics.

Introducing a dynamic approach to manage Split Completion in graphs effectively.

Exploring the unique properties of Praeger-Xu graphs in graph theory.

A new approach improves link prediction accuracy using a mixture of expert models.

A guide to using SHACL shapes with SPARQL for effective data validation.

Subgraphormer combines Subgraph GNNs and Graph Transformers for improved graph learning.

This work explores complex identification problems in mathematics and computer science.

This article discusses strategies for maximizing weights in triangle packing problems.

Exploring the challenge of removing cycles from cubic graphs.

This article explores complex causal frameworks combining classical and quantum theories.

Study of particle dynamics influenced by interconnected neighbors and sparse interactions.