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 ...

Kicking off on Tuesday, the Google I/O developer conference tends to be more than just an extravaganza for the techie set. It’s also a spotlight for the company’s vision and priorities — and shopping ...

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, ...

This paper presents a graph cut approach to the image segmentation task. Considering the image to be a directed graph with two nodes representing the source (object) and the sink (background), the ...

Spatially distributed prediction of streamflow and nitrogen (N) export dynamics is essential for precision management of ...