IEEE

AdaGNN: Adaptive-Boosting Graph Neural Networks for Node Classification

Abstract: Graph neural networks (GNNs) have become the de facto standard for learning over graph-structured data, yet they often falter when labels are scarce, graphs are noisy, or structural patterns ...
PCMag

I Clustered Two Nvidia DGX Spark AI Boxes in My Living Room. Here's What Happened

Daisy-chaining two of Dell's Nvidia GB10 DGX Spark systems didn't just pump up my home AI lab—it fundamentally changed how I ...

Cochlea network model reveals how inner ear may sort sound from noise

Over 70 million people in the U.S. are impacted by hearing loss, and age-related hearing loss is the second most common ...
IEEE

DDGN: Dual-Channel Dual-Mode Graph Networks for Node Classification Under Noisy Topology

Abstract: Graph Neural Networks (GNNs) exploit topological structures—namely, node-to-node connections—to aggregate contextual information, thereby achieving strong performance across diverse domains.