Graph out-of-distribution (OOD) generalization remains a major challenge in graph neural networks (GNNs). Invariant learning, aiming to extract ...
Three questions about next-generation nuclear power, answered These ran the gamut, and while we answered quite a few (and I’m ...
To some, METR’s “time horizon plot” indicates that AI utopia—or apocalypse—is close at hand. The truth is more complicated.
Learn how Microsoft research uncovers backdoor risks in language models and introduces a practical scanner to detect tampering and strengthen AI security.
From autonomous cars to video games, reinforcement learning (machine learning through interaction with environments) can have ...
Herbalife (NYSE:HLF) markets a portfolio centred on nutrition and personal care, including protein shakes, vitamins, energy ...
The Green party has made gains under its leader – but there is also uncertainty ahead ...
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 ...
A decentralized cloud security framework uses attribute-based encryption to enable fine-grained access control without centralized vulnerabilities. By combining cryptographic policy enforcement, third ...
As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models ...
Academic theory recommends very low investment risk near retirement, contrasting sharply with current target date fund (TDF) practices. Most TDFs maintain high-risk allocations—up to 90% in risky ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results