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.

Drug discovery has long been criticized for its slow, costly, and failure-prone nature. Traditional approaches, particularly ...

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 ...

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.

Amazon Neptune just added another query language, openCypher, to its arsenal. That may not sound like a big deal in and of itself, but coupled with updates in machine learning and data science ...

Google’s machine learning-related algorithms. All the major search engines use machine learning in one or many ways. In fact, Microsoft is producing some significant breakthroughs.So are social ...

Both generative AI and machine learning use algorithms to address complex challenges, but generative AI uses more sophisticated modeling and more advanced algorithms to add a creative element ...