The paper elaborates on a technique for using knowledge graphs with machine learning; specifically, a branch of machine learning called reinforcement learning. This is something that holds great ...

With industries increasingly adopting machine learning, it seems likely that knowledge graph technology will also evolve hand-in-hand. As well as being a useful format for feeding training data to ...

As 2022 dawns, knowledge graphs bear the dubious distinction of being at the epicenter of AI and machine learning for two reasons. One is that, unassisted, they are one of the myriad manifestations of ...

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

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 ...

Modeled on the human brain, neural networks are one of the most common styles of machine learning. Get started ... a specialized kind of directed graph. Many neural networks distinguish between ...

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 ...

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