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 ...

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...

Graph-based learning techniques traditionally focus on pairwise relationships, modelling them as edges between two nodes. Hypergraphs generalise this concept by allowing edges—known as hyperedges—to ...

Scientists at ARUP Laboratories have developed an artificial intelligence (AI) tool that detects intestinal parasites in stool samples more quickly and accurately than traditional methods, potentially ...

Biomedical engineers at Duke University have developed a new method to improve the effectiveness of machine learning models. By pairing two machine learning models, one to gather data and one to ...