The 2024 Nobel Prize in Chemistry was recently granted to David Baker, Demis Hassabis and John M. Jumper, renowned for their pioneering works in ...
SM-GNN prunes multi-view GNNs to pure propagation, cutting training time while outperforming prior MKGC accuracies on two ...
Knowledge Graph, Large Language Model, BERT, Knowledge Management, Small and Medium-Sized Enterprises, Accounting, Supply Chain Management Zheng, Y. (2026) Knowledge Graph Application in KM for ...
A new artificial intelligence (AI) method called BioPathNet helps researchers systematically search large biological data ...
A new artificial intelligence (AI) method called BioPathNet helps researchers systematically search large biological data networks for hidden connections – from gene functions and disease mechanisms ...
Researchers at TU Wien are developing a model that interprets opinions not as diametrically opposed poles, but as overlapping ...
Abstract: Recently, topological graphs based on structural or functional connectivity of brain network have been utilized to construct graph neural networks (GNN) for Electroencephalogram (EEG) ...
Graph neural networks in Alzheimer's disease diagnosis: a review of unimodal and multimodal advances
Alzheimer's Disease (AD), a leading neurodegenerative disorder, presents significant global health challenges. Advances in graph neural networks (GNNs) offer promising tools for analyzing multimodal ...
Neural networks are computing systems designed to mimic both the structure and function of the human brain. Caltech researchers have been developing a neural network made out of strands of DNA instead ...
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