Graph neural networks (GNNs) are specialised deep learning architectures designed to operate on data represented as graphs, where entities are modelled as nodes and relationships as edges. In ...

Researchers have developed AdapGNN, a novel model-agnostic framework that addresses the oversmoothing problem in graph neural ...

In a major step toward more reliable AI-assisted molecular design, researchers from National Taiwan University have demonstrated that incorporating uncertainty quantification (UQ) into graph neural ...