Latest Articles for Graphs

A study examines how well LLMs reason with graph data.

A novel approach to enhance sound clarity using advanced deep learning techniques.

A new dataset assesses LLM performance in solving graph-related challenges.

A new tool streamlines access to complex BioPAX datasets for researchers.

Researchers work on a generalized volume operator for quantum gravity analysis.

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

Learn about planar graphs and their significance in various fields.

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

Learn how graphs can simplify knitting patterns and techniques.

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

Examining the minimum colors needed for rainbow cycles in graphs.

Exploring random cell complexes in mathematics and data analysis.

This study explores the unique arrangements of particles under random conditions.

Researchers develop new methods to improve graph generation for various applications.

A look into graph theory and the properties of triangle counts.

Exploring how graphs and hypergraphs reveal relationships in different fields.

A novel approach to shape classification using graph-based techniques.

Discover key concepts of odd edge-colorings and coverings in graph theory.

Examining the role of triangles in graph structures and their implications.

New techniques improve reliability in data transmission using graph structures.

An overview of graph polynomials and their relevance in various fields.

Learn about pinnacle sets and their significance in graph theory.

A new dataset to improve architectural floor plan generation methods for complex buildings.

An examination of location-domination in subcubic graphs and its conjectures.

Exploring the potential of quantum algorithms for complex optimization tasks.

Exploring star-critical Ramsey numbers and their implications in graph coloring.

Exploring the significance and applications of leaf powers in graph theory.

Learn how to switch independent transversals in graphs through small changes.

A look into the properties and importance of matching covered graphs.

A new model predicts traffic accidents by analyzing urban data more effectively.

Examining the complexities of sampling from the Ising model under spectral constraints.

An overview of the properties and implications of Associated Mersenne graphs.

A tool that converts RDF data into usable formats for machine learning.

Explore the unique properties and structures of projective rectangles and their graphs.

xAI-Drop leverages explainability to improve Graph Neural Networks' performance and clarity.

Learn how relational deep learning transforms data analysis for businesses.

Exploring the complexities of Neighborhood Balanced Coloring and its NP-completeness.

A study on the properties and classifications of tetravalent independent-cycle type graphs.

Explore game strategies and graph variations in Dots and Boxes.

A novel approach to enhance understanding of GNN predictions through causal relationships.