1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2024
SpanGNN: Towards Memory-Efficient Graph Neural Networks via Spanning Subgraph Training
Xizhi Gu, Hongzheng Li, Shihong Gao +3
Graph Neural Networks (GNNs) have superior capability in learning graph data. Full-graph GNN training generally has high accuracy, however, it suffers from large peak memory usage…
cs.LG2022★ 1 cited
Distributed Graph Neural Network Training: A Survey
Yingxia Shao, Hongzheng Li, Xizhi Gu +6
Graph neural networks (GNNs) are a type of deep learning models that are trained on graphs and have been successfully applied in various domains. Despite the effectiveness of GNNs,…