Latest Articles for Graph Theory

Investigating the complexities of edge coloring in circle graphs.

A look into symmetric strategy improvement and its challenges in directed graph games.

Exploring RDGSL's innovative approach to reducing noise in dynamic graphs.

A new approach improves dynamic graph modeling for better predictions.

A new approach balances privacy and performance in GNN training.

New methods improve knowledge graph embeddings using literal information.

A look into graph partitioning and the complexities of dominance relations.

Discover how Celtic knots can represent complex graphs creatively.

Exploring the mechanics and capabilities of graph-controlled insertion-deletion systems in computation.

A novel approach improves graph representation learning using non-Euclidean spaces.

This paper examines the size of independent dominating sets in planar triangulations.

Examining how GNNs can improve by modifying irrelevant graph structures.

Leveraging LLMs to make graph data analysis accessible for everyone.

Explore Hamming graphs and their significance in math and research.

Learn how ideas spread through networks using graph burning concepts.

A look into the role of partition diagrams in Combinatorial Hopf Algebra.

This research uses quantum systems to solve complex optimization problems like Max-Cut and MIS.

Methods for local certification of geometric intersection graphs using compact certificates.

Introducing a new method for effective graph clustering using relational information.

A study on how grid homology aids in understanding spatial graphs.

Explore properties of strict outerconfluent graphs and their width parameters.

A look into combinatorial quantum field theory and its applications.

A look into the Erdős problem and its modular implications.

A new approach to graph embedding enhances data analysis through physical force concepts.

Learn how SBBD improves estimation in complete bipartite graphs.

A new framework improves hyperedge prediction accuracy using context-aware aggregation and self-supervised learning.

Explore how Dirichlet eigenvalues shape surface geometry and properties.

This study examines sample complexity in learning DDAGs and their connections over time.

A new GNN approach improves accuracy by reducing over-smoothing.

Exploring guard strategies in bipartite graphs against attacks.

Permutrees blend features of binary trees and permutations to represent complex relationships.

A framework to detect log anomalies by analyzing relationships among events.

Exploring the formation and significance of faces in topological graphs.

Explore the significance of edge ideals in weighted oriented graphs.

This article discusses how graphs are used to create quantum error-correcting codes.

Research reveals limits of MCMC methods in connecting bipartite graphs effectively.

Learn how bipartite treewidth aids in solving complex graph problems efficiently.

A new method for effectively representing and manipulating sparse graphs.

A look into the relationship between Graph Neural Networks and Graph Neural Tangent Kernel.

A look into graph theory's algebraic connectivity, focusing on trees and their structures.