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

We take the opportunity to discuss the database market, graph, and beyond, with CEO and co-founder Claudius Weinberger and Head of Engineering and Machine ... local query execution of multi-model ...

One way to do so is by inserting the outputs of machine learning model predictions back into the graph. “If your models are good, they’re predicting information that’s equally valuable as part of ...

The relational database model was developed in the ... With industries increasingly adopting machine learning, it seems likely that knowledge graph technology will also evolve hand-in-hand.

The paper elaborates on a technique for using knowledge graphs with machine learning; specifically ... To apply the model on industry scale knowledge graphs would require special infrastructure." ...

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

Scientist Yi Nian is sharing his machine ... model to capture critical graph patterns and answers the important question of how to provide a global interpretation for the graph learning procedure.