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.

By learning the relevant features of clinical images along with the relationships between them, the neural network can outperform more traditional methods.

The Enterprise Social Network Graph focusses on people and their relationships with each other. The contrast to the Social Graph is illustrated below: ...

In this graph of a social network created by Brown University Ph.D. student Alice Xia, the red dot represents the target of gossip, the green dot is the person who is sharing gossip, and the black ...

“Graph Convolutional Networks, a type of GNN, are fundamental methods for deep learning on graphs that allow us to learn/understand both the graph structure, or how the graph looks connected ...

Earlier this week I posted about Yahoo's missing piece, it's lack of a social networking hub at the center of its people-centric approach to providing Web-based applications and services. Yahoo's ...

An explainer on the social graph clarifies its significance in understanding online interactions and relationships.

And for anyone skeptical about the social graph, it’s a powerful reminder: people have been at this for quite a while, and modern social networks are barely scratching the surface.

Zuckerberg attributed the power of Facebook to the "social graph, ” the network of connections and relationships between people on the service. He said, "It's the reason Facebook works." ...