Latest Articles for Graph Theory

A new approach to understanding graph similarity using mutual information.

Discover eigenvalues and coboundaries in morphic subshifts for better sequence analysis.

PANDA improves graph neural networks by enhancing information flow without altering graph structure.

This article discusses RDV graphs and methods for finding maximum matchings efficiently.

A clear guide to the concepts and applications of Generalized Bratteli diagrams.

This research enhances GNNs by adapting filters for different node patterns.

Explore the relationships and properties of curve arrangements in mathematics.

Study of perfect matchings in product graphs and their random subgraphs.

Learn how matroids help analyze relationships and independence in various contexts.

HOGE enhances explanations of Graph Neural Networks using cell complexes.

This study presents new algorithms for learning Bayesian networks using online learning techniques.

A look at clustering methods for changing graph structures.

A novel approach to integrate transformers with graph structures for better outcomes.

Exploring strategies to improve Graph Neural Networks and tackle oversmoothing challenges.

This research focuses on enhancing GNNs using self-supervised learning and feature alignment.

A look at how color changes in graphs through a probabilistic process with reversion.

This article explores coloring methods and their implications in graph theory.

This article clarifies the links between effective resistance and optimal transport on graphs.

Examining the properties and applications of metric graphs, focusing on -metric and hyperbolicity.

A new benchmark helps improve GNN performance amid label noise challenges.

New algorithms improve graph alignment speed and accuracy for correlated networks.

Improving DFS algorithms for efficient graph processing under memory constraints.

A look at the behavior of uncommon linear systems and their implications.

Recent findings show classical networks can exhibit quantum-like behaviors.

A look at the challenges and progress in understanding Shannon capacity.

This article presents a new algorithm for solving games on graphs efficiently.

New techniques improve generalization in interconnected data models across various domains.

Exploring complex behaviors of conjugacy classes in dihedral Artin groups.

A look into the connections and structures within the permutahedron.

This article explores the concept of half-space separation in graph convexities.

This study focuses on human perception of graph differences using machine learning.

A new layout method enhances change detection in DAGs across various fields.

A guide to improve the design of node-link diagrams and dynamic graphs.

New method GSSC enhances graph analysis efficiency and effectiveness.

Cometh combines discrete and continuous methods for efficient graph generation.

Examining temporal graphs reveals complexities and methods for efficient problem-solving.

Exploring the links between torus knots and generalized Schroder paths.

A new framework explains node embeddings using simple graph features.

This study focuses on efficient methods for t-matchings in restricted graphs.

An overview of Ramsey numbers and their significance in directed graphs.