Graph neural networks (GNNs) have emerged as a powerful framework for analyzing and learning from structured data represented as graphs. GNNs operate directly on graphs, as opposed to conventional ...

The study of geodetic numbers in graph theory represents a compelling fusion of abstract mathematical ideas with practical applications across network analysis, computational optimisation, and ...

Graph crossing numbers quantify the minimum number of edge intersections in any planar drawing of a graph, an essential parameter in both theoretical and applied graph theory. The study of crossing ...

In just three pages, a Russian mathematician has presented a better way to color certain types of networks than many experts thought possible. A paper posted online last month has disproved a ...