Browsing: Graph Machine Learning

This article discusses strategies for maximizing Graph Machine Learning (GML) performance, including assessing graph quality and utilizing AI-based algorithms and tools. It emphasizes the…

This Special Issue focuses on the most recent advances in the models, algorithms, theories, and applications of Graph Machine Learning (GML), both in academic…

ArangoDB has released ArangoGraphML, a fully managed graph machine learning platform, designed to make it easier to integrate machine learning with graph data. The…

Researchers from Stanford have recently proposed a new pretraining framework called PRODIGY, which enables in-context learning over graphs. PRODIGY formulates in-context learning over graphs…