Graph neural networks (GNNs) have emerged as a powerful framework for analyzing and learning from structured data represented as graphs. GNNs operate directly on graphs, as opposed to conventional ...

Graph matching remains a core challenge in computer vision, where establishing correspondences between features is crucial for tasks such as object recognition, 3D reconstruction and scene ...

A research team has developed a new technology that enables to process a large-scale graph algorithm without storing the graph in the main memory or on disks. A KAIST research team has developed a new ...

Graphs have been around forever, but the internet has given them new life. It's refocused our attention on the use of graph concepts for information search as an option to traditional hierarchical ...

Graph databases are an 18th century concept with a host of modern applications. Used for tasks as diverse as dating sites and fraud detection, graph technology works by looking at relationships, not ...

The latest trends in software development from the Computer Weekly Application Developer Network. This is a guest post for the Computer Weekly Developer Network written by Henrik Plate in his capacity ...