Graph database developer Neo4j Inc. is upping its machine learning game today with a new ... that can be run against a graph beyond the basic set that was included when the library was introduced ...

The meaning of the term is not precisely set-in-stone – for example ... With industries increasingly adopting machine learning, it seems likely that knowledge graph technology will also evolve ...

but also other approaches that are not neural nets, such as set theory. The idea is that graph networks are bigger than any one machine-learning approach. Graphs bring an ability to generalize ...

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

The core product is a knowledge graph they claim ... Look carefully at the ROI machine learning brings to your systems, it could be worth waiting for a more mature set of solutions.

The updates expand the role for its tools, as TigerGraph’s product is becoming more of a data analytics and AI platform than just a mechanism for storing graph data. “Our biggest enterprises ...

Since their reply was "no," he set out to do that with Weaviate. NLP machine learning models ... simple for people to access graphs so they have a very short learning curve, GraphQL becomes ...

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 ...