Graph neural networks (GNNs) have emerged as a powerful framework for analyzing and learning from structured data represented as graphs. GNNs operate directly on graphs, as opposed to conventional ...

Research team led by Chuliang Weng introduces D2-GCN, a groundbreaking disentangled graph convolutional network that dynamically adjusts feature channels for enhanced node representation ...

BingoCGN, a scalable and efficient graph neural network accelerator that enables inference of real-time, large-scale graphs through graph partitioning, has been developed by researchers at ...

Google’s June 2025 Core Update just finished. What’s notable is that while some say it was a big update, it didn’t feel ...