Nature

Efficient federated graph aggregation for privacy-preserving GNN-based session recommendation

Graph Neural Networks (GNN) have attracted increasing attention due to their efficient performance in recommendation systems. However, applying GNNs in session-based recommendations with emerging ...
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New framework reduces memory usage and boosts energy efficiency for large-scale AI graph analysis

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 the ...
Nature

An efficient intelligent transportation system for traffic flow prediction using meta-temporal hyperbolic quantum graph neural networks

Considering, growing quantity of automobiles on the road, modern transportation schemes face significant challenges such as gridlock, frequent accidents, thenconservational deterioration. When taking ...
EurekAlert!

Real-time, large-scale graph neural network inference through BingoCGN

BingoCGN employs cross-partition message quantization to summarize inter-partition message flow, which eliminates the need for irregular off-chip memory access and utilizes a fine-grained structured ...