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, ...

Expect to hear increasing buzz around graph neural network use cases among hyperscalers in the coming year. Behind the scenes, these are already replacing existing recommendation systems and traveling ...

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 ...

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 ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More A team of chemistry, life science, and AI researchers are using graph ...

Deep Neural Networks are the more computationally powerful cousins to regular neural networks. Learn exactly what DNNs are and why they are the hottest topic in machine learning research. The term ...