Graph neural networks (GNNs) are a relatively recent development in the field of machine learning. Like traditional graphs, a core principle of GNNs is that they model the dependencies and ...

BingoCGN, a scalable and efficient graph neural network accelerator that enables inference of real-time, large-scale graphs through graph partitioning, has been developed by researchers at ...

A team of chemistry, life science, and AI researchers are using graph neural networks to identify molecules and predict smells. Models made by researchers outperform current state-of-the-art ...

Arriving at this graph neural network destination took the combined work of Google as well as Amazon, Waymo, and Sea AI Lab, but now provides Google Maps with a far more accurate ETA and the ability ...

Facebook releases AI Habitat, a powerful simulator for training neural networks - SiliconANGLEAI Habitat might not be the first simulator built with machine learning projects in mind, but it’s ...

As with the GP, some simulation software could be used to get a ground truth estimate of the lifting force generated by the wing. The combination of the mesh data and resulting lifting force ...

GraphCast utilizes what researchers call a "graph neural network" machine-learning architecture, trained on over four decades of ECMWF's historical weather data. It processes the current and six ...