Undirected Graph

Undirected graphs, mathematical structures representing relationships between interconnected entities, are central to numerous fields, with research focusing on efficient representation, analysis, and manipulation of these structures. Current research emphasizes developing robust algorithms for tasks like clique detection (e.g., CLIPPER+), optimal transport-based graph comparison, and efficient graph embedding techniques for node classification, often leveraging spectral methods or nonnegative matrix factorization. These advancements have significant implications for diverse applications, including network analysis, computer vision, and machine learning, by enabling more accurate modeling and analysis of complex systems.