A new open-access study reports that fusing attribute features with graph structure and training classifiers collaboratively ...

Graphs are everywhere. In discrete mathematics, they are structures that show the connections between points, much like a public transportation network. Mathematicians have long sought to develop ...

Researchers have introduced distributed algorithms that detect communities in a class of networks where time is built ...

Graph colouring, the assignment of colours to the vertices of a graph so that no two adjacent vertices share the same colour, represents a canonical NP-hard combinatorial optimisation problem with ...

This book offers a refreshing approach to complex concepts by blending humor, imaginative examples, and practical Python implementations to reveal the power and versatility of graph based ...

Machine learning, task automation and robotics are already widely used in business. These and other AI technologies are about to multiply, and we look at how organizations can best take advantage of ...

This research introduces quantum graph networks for max-clique detection, overcoming trainability issues with compositional ...

This is a sequence of lessons which covers the definitions in graph theory and the planarity algorithm. It includes a definitions crossword and smart notebook files for both sets of lessons. A bundle ...

A professor has helped create a powerful new algorithm that uncovers hidden patterns in complex networks, with potential uses in fraud detection, biology and knowledge discovery. University of ...