Latest Articles for Graph Theory

This article discusses methods for assigning edge weights based on graph structure.

A look into graphs with a single Hamiltonian cycle and their properties.

A look at separability and its implications in automatic and recognizable relations.

Exploring the impact of graph structure on quantum annealing effectiveness.

This study examines how hidden features in graphs can predict node outcomes.

Introducing MetaSRL++ for improved language meaning representation.

A look into sparse graphs, degeneracy, and induced paths.

A deep dive into shortest path algorithms and their efficiency.

A study on language models' ability to handle graph tasks with new benchmarks.

Learn about radio labeling and its significance in minimizing interference in communication systems.

Examining the links between Hessenberg varieties and graph colorings.

An examination of geodesics in hyperbolic surfaces and their unique properties.

This study shows how directed edges enhance GNN performance, especially in heterophilic graphs.

This research enhances node classification using label non-uniformity in graph neural networks.

A practical guide to the Saltbox-Roof Probability Distribution and its applications.

An examination of contrastive learning's unique data clustering methods.

High dimensional expanders connect diverse fields, revealing hidden relationships in mathematics.

A look into how geometrical shapes relate to group theory.

This study explores the unique packing colorings of trees in graph theory.

A new model improves graph transformation predictions across varied structures.

An overview of constraint satisfaction problems and their complexities.

Introducing a novel model for efficient graph clustering using geometric principles.

New methods improve data analysis in heterogeneous graphs for better insights.

A new framework enhances performance in graph data processing.

Exploring efficient distance sensitivity oracles for networks with potential edge failures.

This study investigates graphons under specific constraints related to edge and 2star densities.

Exploring the significance of non-vanishing minors in eigenvectors of random matrices and graphs.

A new method improves predictions for large graphs while reducing memory use.

A new semi-supervised framework improves predictions for under-represented graph properties.

Examining effective strategies for playing the graph coloring game on multipartite graphs.

This article examines electron behavior and energy minimizers in atomic models.

A new framework enables models to learn from graphs using in-context techniques.

A new framework improves link prediction and provides understandable explanations.

Exploring the reconfigurability of arc-disjoint arborescences and their implications.

Learn about the Weisfeiler-Leman algorithm and its impact on graph isomorphism.

This research shows solvability in key semigroup problems for certain metabelian groups.

A look into relation algebras and the k-consistency method for network satisfaction.

Researchers bridge graphs and logic to enhance clarity in logical reasoning.

Gelato offers a simpler, effective method for link prediction in networks.

Learn how to analyze causal structures in complex data through directed graphs.