The paper elaborates on a technique for using knowledge graphs with machine learning; specifically ... facts of the graph in a plain .txt file and read the entire graph into memory when running ...

Scientist Yi Nian is sharing his machine-learning expertise with the world in his latest co-authored publication, “Globally Interpretable Graph Learning ... can be read online in full detail.

Also: Google Next 2018: A deeper dive on AI and machine learning advances The paper explicitly draws upon work for more than a decade now on "graph neural networks." It also echoes some of the ...

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 ...

A new study in Small introduces OptiMate, a machine learning model that predicts optical properties and identifies ...

This is known as a knowledge graph. Knowledge graphs are not new ... and products are launched. It uses more machine-learning algorithms to fuse new facts with old, creating new connections ...

Their market-leading automation and machine learning capabilities for data structuring combined with our graph-based enterprise operating system will be a powerful combination. We're looking ...