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 ...

Deep Learning and Machine Learning has made breakthroughs in recent years. There is tens of billions of dollars going into development of the new AI. Google and Deep Mind are recognizing that Deep ...

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 ...

Douglas Adams once wrote of a Holistic Detective Agency. The central character in this story, Dirk Gently, was able to solve cases with his understanding of the fundamental interconnectedness of ...

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 ...

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 ...