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 ...
As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models ...
As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models ...
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 ...
A decentralized cloud security framework uses attribute-based encryption to enable fine-grained access control without centralized vulnerabilities. By combining cryptographic policy enforcement, third ...
Search patents reveal how AI search systems interpret intent, evaluate content passages, and build brand understanding in ...
The Green party has made gains under its leader – but there is also uncertainty ahead ...
Herbalife (NYSE:HLF) markets a portfolio centred on nutrition and personal care, including protein shakes, vitamins, energy ...
From the Third Intermediate Period through the Late, Ptolemaic, and Roman eras, ancient Egyptian private funerary monuments underwent marked architectural and ritual reconfigurations ...
India's Ponzi problem has quietly turned into a full-fledged industry, and a large part of the factory now runs offshore ...
Graph out-of-distribution (OOD) generalization remains a major challenge in graph neural networks (GNNs). Invariant learning, aiming to extract ...
Abstract: The task of network alignment aims to identify corresponding nodes across multiple networks, with applications in various fields such as social network analysis and bioinformatics.
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