Nature

Graph Neural Networks and Network Embedding Techniques

Graph neural networks (GNNs) have rapidly emerged as a central methodology for analysing complex datasets presented as graphs, where entities are interconnected through diverse relationships. By ...
EurekAlert!

PolyU develops novel AI graph neural network models to unravel interdisciplinary complexities in image recognition and neuroscience

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 ...
Finextra

Graph Neural Networks and GraphRAG: Navigating Open-World Complexity in Finance

Graph Neural Networks (GNNs) and GraphRAG don’t “reason”—they navigate complex, open-world financial graphs with traceable, multi-hop evidence. Here’s why BFSI leaders should embrace graph-native AI ...
Bloomberg L.P.

Supply chain momentum strategies with graph neural networks

Supply chain data has been studied as a potential source of investment opportunity for years. Many possible theoretical approaches can be employed when considering how an investor could leverage ...
VentureBeat

LinkedIn creates PASS to tailor graph neural networks for social media

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now Graphs are, quite simply, a universal ...
Devdiscourse

Big Data and AI propel geoscience into new digital era

A new study published in the journal Minerals sheds light on this sweeping shift. Titled Big Data and AI in Geoscience: From ...