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 ...
LAFAYETTE, Calif., Feb. 8, 2021 — Franz Inc., an Artificial Intelligence (AI) innovator and leading supplier of Graph Database technology for AI Knowledge Graph Solutions, today announced AllegroGraph ...
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 ...
Researchers at Shanghai Jiao Tong University have made a groundbreaking discovery in the field of Temporal Knowledge Graphs (TKGs), challenging the ...
PARIS, Oct. 28, 2021 – Pasqal, developers of neutral atom-based quantum technology, today announced the publication of a scientific paper in the peer-reviewed APS Physics journal Physical Review A ...
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 ...
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