Knowledge representation is a fundamental aspect of AI, which allows machines to understand, think, and even make choices ...
SM-GNN prunes multi-view GNNs to pure propagation, cutting training time while outperforming prior MKGC accuracies on two ...
A new artificial intelligence (AI) method called BioPathNet helps researchers systematically search large biological data ...
Transformer on MSNOpinion
Against the METR graph
METR’s benchmark has become a bellwether of AI capability growth, but its design isn’t up to the task, argues Nathan Witkin ...
Morning Overview on MSN
Quantum walks explained, and why they could change everything
Quantum walks sound abstract, but they sit at the center of a very concrete race: who will harness quantum mechanics to solve ...
Abstract: This study aims to optimize the existing retrieval-augmented generation model (RAG) by introducing a graph structure to improve the performance of the model in dealing with complex knowledge ...
Credit: Image generated by VentureBeat with FLUX-pro-1.1 Without data, enterprise AI isn't going to be successful. Getting all the data in one place and having the right type of data tools, including ...
Abstract: Multivariate time series anomaly detection (MTSAD) plays a crucial role in the Internet of Things (IoT) to identify device malfunction or system attacks. Graph neural networks (GNN) are ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Protein function prediction is essential for elucidating biological processes and ...
To stay visible in AI search, your content must be machine-readable. Schema markup and knowledge graphs help you define what your brand is known for. New AI platforms, powered by generative ...
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