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.

This article explores what knowledge graphs are, why they are becoming a favourable data storage format, and discusses their potential to improve artificial intelligence and machine learning ...

SAN FRANCISCO, Oct. 11, 2023 — ArangoDB, a company behind the most complete and scalable graph data and analytics platform, announced the GA release of ArangoGraphML, a fully managed and intuitive ...

Combining graphs and machine learning has been getting a lot of attention lately, especially since the work published by researchers from DeepMind, Google Brain, MIT, and the University of Edinburgh.

Scientist Yi Nian is sharing his machine-learning expertise with the world in his latest co-authored publication, “Globally Interpretable Graph Learning via Distribution Matching.” SEATTLE ...

Understanding, Knowing, and Connecting via Knowledge GraphsKnowledge graphs grant us new and different ways of visualizing our data. The technology connects disparate entities and surfaces the ...

More information: Jiaxin Xu et al, Superior polymeric gas separation membrane designed by explainable graph machine learning, Cell Reports Physical Science (2024). DOI: 10.1016/j.xcrp.2024.102067.

Next-generation graph data and analytics platform now with machine learning and data science features to accelerate innovation. SAN FRANCISCO, Oct. 11, 2023 /PRNewswire/ -- ArangoDB, the company ...

SAN FRANCISCO, Oct. 11, 2023 /PRNewswire/ -- ArangoDB, the company behind the most complete and scalable graph data and analytics platform, announced the GA release of ArangoGraphML, a fully ...