Mathematicians have long sought to develop algorithms that can compare any two graphs. In practice, many ...

First is Node2Vec, a popular graph embedding algorithm that uses neural networks to learn continuous feature representations for nodes, which can then be used for downstream machine learning tasks.

Two computer scientists found — in the unlikeliest of places — just the idea they needed to make a big leap in graph theory.

A new algorithm efficiently solves the graph isomorphism problem, which has puzzled computer scientists for decades.

Second, via modern algorithmic techniques: parameterizing polynomial algorithms to run in time linear in the graph size and superlinear only in a small parameter; dynamic algorithms that, as the input ...

The gFTP algorithm constructs binary recurrent neural networks with user-defined dynamics by adjusting non-realizable graphs and solving linear problems. This innovative approach enhances the ...

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.

A machine-learning algorithm, Weighted Graph Anomalous Node Detection (WGAND), has been developed to identify key proteins in human tissues by analyzing protein-protein interaction networks.

Bluesky may build a clever system featuring custom feeds and algorithmic choice, but its impact may be limited if the app remains closed.