Latest Articles for Graph Theory

Path-LLM offers new ways to create meaningful graph embeddings for diverse applications.

Research focuses on optimizing the stable set problem in various graph types.

A look into association schemes and their role in mathematical analysis.

A look at nested conditions and their impact on graph transformations.

EggNet enhances particle tracking accuracy using evolving graph-based techniques.

Exploring the unique properties of random spanning trees in graph theory.

A new method improves GNN architecture design using insights from language models.

This framework enhances predictions by focusing on real causal relationships in event data.

This article examines testing methods for ensuring accuracy in graph databases.

A look into the significance and statistical behavior of graph cuts.

Study clustering patterns in graph colouring with strong products and bounded properties.

Explore the significance and complexity of orthogonality dimension in graph theory.

A new algorithm improves the search for multiple shortest paths in directed graphs.

Exploring unique characteristics of regular graphs, 2-factors, and Hamiltonian circuits.

Exploring the connections between balanced incomplete block designs and generalized quadrangles.

A study on algorithm performance for the Max-Cut problem.

Two players strategize to control a graph's vertices in a dominator-staller game.

GrassNet uses State Space Models for adaptive filtering in graph neural networks.

Explore the basics and importance of graph structures and their properties.

Exploring the relationships between theta graphs and diffeomorphic mapping classes.

A study on descents, inversions, and their implications in permutations.

New methods boost graph node classification accuracy with limited labeled data.

This article investigates LLM performance on graph-related reasoning tasks.

A new method addresses challenges in Graph Neural Networks with heterophilic data.

Introducing GraphSPNs to enhance graph-based probabilistic tasks and molecule generation.

Explore the link between frames and graphs to understand scalability.

New polynomial methods simplify tree isomorphism verification.

This article examines how symmetrization links polytopes and posets in mathematics.

Learn how distance oracles optimize distance queries in large networks.

Learn how Graph Neural Networks improve quantum error correction techniques.

An overview of chromatic and cochromatic numbers in graph theory.

Exploring the role of quantum machine learning in advancing data analysis techniques.

Explore the dynamics of a strategic game played on graphs with unique rules.

An overview of Sidorenko's conjecture and its impact on graph properties.

GraphFSA enhances machine learning by applying finite state automata to graph structures.

New strategies enhance color assignment in virtual graphs despite communication constraints.

Research enhances understanding of random Turan numbers and hypergraph structures.

This paper examines the depth and noise effects in poly-GNNs for semi-supervised learning.

A look into the relationship between tiered trees and parking functions in mathematics.

This article discusses the down-up walk method for analyzing graph matchings and its efficiency.