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 ...

You wouldn’t change up your entire production process based on sales from just a couple of locations, and you wouldn’t lower auto insurance premiums across the board because collision rates went down ...

The analysis of social networks and graphs has become increasingly crucial as our understanding of complex systems grows. Modern research has focused on robust sampling techniques that help capture ...

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, ...

The cybersecurity industry loves a good quote. At every conference, buried among the slide decks littered with questionable quotes from Sun Tzu's Art of War, you will occasionally strike gold and see ...

DPABINet, a sophisticated enhancement of the DPABI software suite, streamlines the intricate analysis of brain networks through fMRI data, providing researchers of all expertise levels with ...

Showing numerical data graphically is crucial whenever there are more than half-a-dozen data points – the human mind (at least of most of us) simply can’t grasp an array of values and see the ...

A super geeky topic, which could have super important repercussions in the real world. That description could very well fit anything from cold fusion to knowledge graphs, so a bit of unpacking is in ...