Google today released TensorFlow Graph Neural Networks (TF-GNN) in alpha, a library designed to make it easier to work with graph structured data using TensorFlow, its machine learning framework.

With graphs becoming more pervasive and richer with information, and artificial neural networks becoming more popular and capable, GNNs have become a powerful tool for many important applications.

Soft-GNN: Towards Robust Graph Neural Networks via Self-adaptive Data Utilization. Article Publication Date. 15-Apr-2025. ... Frontiers of Computer Science DOI 10.1007/s11704-024-3575-5.

BingoCGN, a scalable and efficient graph neural network accelerator that enables inference of real-time, large-scale graphs ...

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 ...

AI, for both mobile and fixed solutions, announced that is now working on Graph Neural Network based ... including its GopherInsight™ wireless mesh network technology platform and its Avant! ...

Recurrent neural networks, or RNNs, are a style of neural network that involve data moving backward among layers. This style of neural network is also known as a cyclical graph .

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, ...