Graph algorithms constitute a fundamental area of computational research that focuses on the analysis and manipulation of graph structures, which represent systems of interconnected entities. In ...

The graph colouring problem, a classic NP-hard challenge, is central to many practical applications such as scheduling, resource allocation and network management. Recent advances have seen the ...

Back in the hazy olden days of the pre-2000s, navigating between two locations generally required someone to whip out a paper map and painstakingly figure out the most optimal route between those ...

SAN FRANCISCO, April 24, 2019 /PRNewswire/ -- SPARK + AI SUMMIT – Neo4j, the leader in graph database technologies, announced today the launch of Graph Algorithms: Practical Examples in Apache Spark & ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...