Identity management for cybersecurity is inherently a complex graph problem due to the vast, dynamic, and interconnected nature of modern IT environments. The Fast Company Executive Board is a private ...

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...

Graph out-of-distribution (OOD) generalization remains a major challenge in graph neural networks (GNNs). Invariant learning, aiming to extract invariant features across varied distributions, has ...

Giulia Livieri sets out remarkable new research with results that clarify how learning works on complex graphs and how quickly any method (including Graph Convolutional Networks) can learn from them, ...

The foundation for Knowledge Graphs and AI lies in the facets of semantic technology provided by AllegroGraph and Allegro CL. AllegroGraph is a graph based platform that enables businesses to extract ...

Graphs are everywhere. In discrete mathematics, they are structures that show the connections between points, much like a public transportation network. Mathematicians have long sought to develop ...

Text mining and knowledge graphs connect cell-culture parameters to glycosylation for faster bioprocess optimization.

Editorial Note: Talk Android may contain affiliate links on some articles. If you make a purchase through these links, we will earn a commission at no extra cost to you. Learn more. The visualization ...

Hybrid clouds create blind spots, exacerbate the alert fatigue problem, and make it more difficult to detect an intruder’s lateral movements. Artificial intelligence, combined with security graphs, ...