Graph neural networks help to process and analyze complex graph-structured data, unlocking new possibilities across a wide range of applications.

Graph neural networks are very powerful tools. They have already found powerful applications in domains such as route planning, fraud detection, network optimization, and drug research.

I co-created Graph Neural Networks while at Stanford. I recognized early on that this technology was incredibly powerful. Every data point, every observation, every piece of knowledge doesn’t exist in ...

Franz Inc., an early innovator in AI and leading supplier of graph database technology, is releasing AllegroGraph 7.2, providing organizations with essential data fabric tools, including graph neural ...

Franz’s AllegroGraph 7.2 Powers Enterprise Data Fabrics with Graph Neural Networks, Virtual Graphs and Streaming Graph Pipelines ...

Graph Neural Networks are on the path to becoming more mainstream, with exciting opportunities for the maturation of essential operations across message passing such as scatters, gathers, segmented ...

Researchers have developed a new tool, bimodularity, that adds directionality to community detection in networks.