Latest Articles for Graph Theory

Examining sparse outerstring graphs reveals efficient solutions for complex problems.

Explore how degree sequences affect random graph characteristics.

A look into Ramsey numbers, hypergraphs, and coloring in combinatorics.

This study examines the presence of clique subdivisions within various graph structures.

A new approach to solve the Maximum Independent Set problem without training data.

Explore the intricacies of reachability in temporal graphs and their unique challenges.

Learn about planar graphs and their significance in various fields.

Researchers enhance GNNs for better understanding of complex graph structures.

Exploring the crossing number problem in graphs and its real-world applications.

A look into triangle-free triple systems and their properties in combinatorial mathematics.

An exploration of how paths connect through systematic flips.

This research focuses on finding even-length paths in directed graphs and their applications.

This article examines the challenges in finding specific subgraphs in graph theory.

A new framework that enhances MLP performance in graph classification using GNN knowledge.

New methods aim to simplify the Steiner Tree problem for various applications.

A new solver enhances solution speed and quality for combinatorial optimization tasks.

Examining how random walks impact solutions in constraint satisfaction problems.

Introducing a simple inverse power method for solving balanced cut problems efficiently.

Energy GNNs improve communication and adaptation in multi-agent systems.

A new approach using knowledge enhances efficiency in learning from relational graphs.

Explore graph properties, coloring challenges, and their impact on various fields.

GraphArena evaluates LLM performance on graph problems using real-world data.

A look at nonparametric regression methods using geometric graphs and Bayesian approaches.

Commute Graph Neural Networks improve understanding of directed graphs through enhanced relationship insights.

This article explores the link between resonance graphs and daisy cubes.

HIGHT enhances language models by using hierarchical information from graph data.

A new approach to enhancing Graph Neural Networks through complex vertex representation.

A look into the dimer arrangements and their applications in various fields.

A new framework improves graph classification by focusing on core features.

Exploring the impact of weak random walks on network analysis.

Examining the minimum colors needed for rainbow cycles in graphs.

Examining the complexity of graph orientation and its relation to tournaments.

A look into graphs, their structures, and the implications for data analysis.

Exploring the relationship between chambers and independent sets in geometry using Kneser graphs.

Researchers enhance graph understanding through learned distances and node features.

This article explores geodetic Cayley graphs related to finite groups and their properties.

Exploring Hamilton paths and their existence in cube hypergraphs.

Exploring methods to efficiently color 3-colorable graphs in computer science.

Exploring differential encoding and its impact on graph learning models.

This article examines chambers, vector spaces, and the Erdős-Ko-Rado problem in combinatorics.