Graph algorithms constitute a pivotal component of modern computational science, underpinning diverse applications ranging from transportation optimisation and telecommunications to social network ...

Distributed algorithms for graph problems represent a vibrant area of study that addresses the challenges of decentralised computation across interconnected networks. By partitioning complex graph ...

Efficiently and quickly chewing through one trillion edges of a complex graph is no longer in itself a standalone achievement, but doing so on a single node, albeit with some acceleration and ...

PageRank is named after Google co-founder Larry Page and is used to rank websites by their importance and quality. Simplified, this is done by assuming that the more links there are to a website, the ...

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Classic Graph Convolutional Networks (GCNs) often learn node representation holistically, which would ignore the distinct impacts from different neighbors when aggregating their features to update a ...

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 ...

Victor Lee is director of product management at TigerGraph. Graph databases excel at answering complex questions about relationships in large data sets. But they hit a wall—in terms of both ...

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 ...