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 ...
At a time when every enterprise looks to leverage generative artificial intelligence, data sites are turning their attention to graph databases and knowledge graphs. The global graph database market ...
This course focuses on computational and modeling challenges in real world graphs (networks), with a particular emphasis on key advancements in graph representation and its applications. At the end of ...
Daimler Truck uses graph technology to untangle its IT estate and gains long-lasting operational windfall - SiliconANGLE ...
MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, released learnable quantum spectral filter technology for hybrid graph neural networks. This ...
There is a healthy relationship between large language models (LLMs) and graph databases, which are used to draw in information across different networks of data, according to Jim Webber, chief ...
How do you solve the age-old data integration issue? We addressed this in one of the first articles we wrote for this column back in 2016. It was a time when key terms and trends that dominate today's ...
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