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

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 ...

Neural modeling and simulation are foundational tools in computational neuroscience, enabling researchers to explore how neural systems process information, ...

To address these limitations, we introduce a novel framework: the Molecular Merged Hypergraph Neural Network (MMHNN). MMHNN ...

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 ...