Excel's People Graph add-in turns simple tables into clean, icon-based visuals that automatically update when your data ...

One of the greatest weaknesses of AI agents that read and understand vast amounts of enterprise data is "hallucination"—the generation of plausible-sounding but factually incorrect information. KAIST ...

Schneider Electric is acquiring Cognite, a provider of Agentic AI solutions, at a hefty 18.2 revenues. Cognite is growing ...

BENGALURU, IN / ACCESS Newswire / July 3, 2026 / Reo.Dev, the world's only intent platform purpose-built for DevTools companies, today announced a major milestone with its Developer Knowledge Graph ...

Abstract: Graph convolutional network (GCN) has shown potential in hyperspectral image (HSI) classification. However, GCN is a transductive learning method, which is difficult to aggregate the new ...

This repository for the paper 📘: A Survey of Deep Graph Learning under Distribution Shifts: from Graph Out-of-Distribution Generalization to Adaptation. The README file here maintains a list of ...

Context graphs, graph memory, and ontologies for AI are converging. What does this mean for enterprise AI in 2026?

Google Cloud Summit came to London last week, and we took the opportunity to sit down with database execs Sailesh ...

Abstract: Six-degree-of-freedom (6-DOF) pose estimation from feature correspondences remains a popular and robust approach for 3-D registration. However, heavy outliers that existed in the initial ...

Heterogeneous Graph Transformer is a graph neural network architecture that can deal with large-scale heterogeneous and dynamic graphs. You can see our WWW 2020 paper “Heterogeneous Graph Transformer” ...