EurekAlert!

Chongqing Medical University team: dual-branch graph attention network enables personalized prediction of ECT efficacy in adolescent depression

Major Depressive Disorder (MDD) is a leading cause of disability among adolescents, yet the efficacy of Electroconvulsive Therapy (ECT)—a gold-standard treatment for severe cases—varies significantly ...

Why Structure, Not Scale, Will Be AI’s Next Bottleneck

Progress will come from systems that can combine language understanding with explicit spatial and structural reasoning.
Tech Xplore

New graph attention network models higher-order relationships in complex graph data

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 ...
EurekAlert!

Simplified multi-view graph neural network for multilingual knowledge graph completion

SM-GNN prunes multi-view GNNs to pure propagation, cutting training time while outperforming prior MKGC accuracies on two ...
AlphaGalileo

A Survey of Geometric Graph Neural Networks: Data Structures, Models and Applications

The 2024 Nobel Prize in Chemistry was recently granted to David Baker, Demis Hassabis and John M. Jumper, renowned for their pioneering works in ...

New AI uncovers hidden patterns in biomedical knowledge graphs

A new artificial intelligence (AI) method called BioPathNet helps researchers systematically search large biological data ...
Scientific Research Publishing

Geo-Refined Point Transformer: Coordinate-Aware Excitation and Positional Upsampling for 3D Scene Segmentation ()

The proposed Coordinate-Aware Feature Excitation (CAFE) module and Position-Aware Upsampling (Pos-Up) module both adhere to ...