Graphs are a ubiquitous data structure and a universal language for representing objects and complex interactions. They can model a wide range of real-world systems, such as social networks, chemical ...

Giulia Livieri sets out remarkable new research with results that clarify how learning works on complex graphs and how quickly any method (including Graph Convolutional Networks) can learn from them, ...

Graph data, e.g., social and biological networks, financial transactions, knowledge graphs, and transportation systems are pervasive in the natural world, where nodes are entities with features, and ...

Graph machine learning (or graph model), represented by graph neural networks, employs machine learning (especially deep learning) to graph data and is an important research direction in the ...

Researchers report that the integration of machine learning and Internet of Things (IoT) technologies is enabling a new generation of intelligent industrial environments capable of real-time ...