I co-created Graph Neural Networks while at Stanford. I recognized early on that this technology was incredibly powerful.

Researchers have developed a new tool, bimodularity, that adds directionality to community detection in networks.

Graph-structured data are pervasive in the real-world such as social networks, molecular graphs and transaction networks.

Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and other artificial intelligence (AI) models, learn to make accurate ...

But as mobile hardware advances, Machine Learning (ML) techniques, particularly Graph Neural Networks (GNNs), are emerging as a powerful, efficient alternative to emulate physics on mobile. GNNs are ...

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, ...