Graph algorithms and sparsification techniques have emerged as pivotal tools in the analysis and optimisation of complex networked systems. These approaches focus on reducing the number of edges in a ...

Graph labeling is a central topic in combinatorial optimisation that involves assigning numerical or categorical labels to vertices or edges of a graph subject to specific constraints. This framework ...

Two computer scientists found — in the unlikeliest of places — just the idea they needed to make a big leap in graph theory. This past October, as Jacob Holm and Eva Rotenberg were thumbing through a ...

A couple of weeks ago, I attended and spoke at the first stop in the Neo4j GraphTour in Washington D.C. and I was able to get the best answer yet to a question that I’d been pondering: what’s the ...

A puzzle that has long flummoxed computers and the scientists who program them has suddenly become far more manageable. A new algorithm efficiently solves the graph isomorphism problem, computer ...

On the 19th of February 2025, M.Sc. Andreas Grigorjew defends his PhD thesis on Algorithms and Graph Structures for Splitting Network Flows, in Theory and Practice. The thesis is related to research ...

Scalable Graph Algorithms for Bioinformatics using Structure, Parameterization and Dynamic Updates, ERC Consolidator Grant, 9/2025-8/2030 Sequencing technologies have developed to be cheap and ...

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 ...

Reduced link graphs are a way that search engines can identify high quality websites and remove low quality spam sites from the link ranking calculation. Published research demonstrates that reduced ...