Other than giving us an appreciation how little difference going eight miles an hour over the speed limit makes, that ETA service is a remarkable invention — and one that takes a hell of a lot of ...

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 ...

For instance, the application of NAS to Graph Neural Networks (GNNs) is explored in depth, with the authors discussing the unique challenges and opportunities presented by non-Euclidean data.

The Blaize GSP architecture and Blaize Picasso software development blend dynamic data flow methods and graph computing models with fully programmable proprietary SOCs. This allows Blaize computing ...

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 ...