The core product is a knowledge graph they claim has mapped “over ... they have released a short report about the state of the machine learning industry. The key slide I saw in the report ...

Molecular machine learning (ML) underpins critical workflows in drug discovery, material science, and catalyst optimization ...

Gremlin has a lot going for it, as it has nearly ubiquitous support, and offers a lot of control ... development in graph databases: integration of data science and machine learning features.

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 ...

proposed a graph machine learning model, namely TREE, based on the Transformer framework. With this novel Transformer-based ...

This course focuses on computational and modeling challenges in real world graphs (networks), with a particular emphasis ... Students should have a strong interest in conducting (or learning how to ...