Graph neural networks (GNNs) have rapidly emerged as a central methodology for analysing complex datasets presented as graphs, where entities are interconnected through diverse relationships. By ...

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 ...

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now Graphs are, quite simply, a universal ...

A technical paper titled “Accelerating Defect Predictions in Semiconductors Using Graph Neural Networks” was published by researchers at Purdue University, Indian Institute of Technology (IIT) Madras, ...

Nanoengineers have developed new deep learning models that can accurately predict the properties of molecules and crystals. The models can enable researchers to rapidly scan the nearly-infinite ...

The internal social graph inside companies will be quite different and far more useful than existing public counterparts. A social graph in the public realm represents the network we have created by ...

BingoCGN employs cross-partition message quantization to summarize inter-partition message flow, which eliminates the need for irregular off-chip memory access and utilizes a fine-grained structured ...

To be honest, I hate politics — especially on a national level. But local politics is different. There are no Sunday talk shows, press people to hide behind, or escaping your neighbors over the ...