16 citations · 42 across the 25 of their papers we have counts for
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cs.LG2023★ 1 cited
Accelerating Scalable Graph Neural Network Inference with Node-Adaptive Propagation
Xinyi Gao, Wentao Zhang, Junliang Yu +4
Graph neural networks (GNNs) have exhibited exceptional efficacy in a diverse array of applications. However, the sheer size of large-scale graphs presents a significant challenge…
cs.LG2023★ 1 cited
Graph Condensation for Inductive Node Representation Learning
Xinyi Gao, Tong Chen, Yilong Zang +4
Graph neural networks (GNNs) encounter significant computational challenges when handling large-scale graphs, which severely restricts their efficacy across diverse applications. T…
cs.LG2023★ 2 cited
Semantic-aware Node Synthesis for Imbalanced Heterogeneous Information Networks
Xinyi Gao, Wentao Zhang, Tong Chen +3
Heterogeneous graph neural networks (HGNNs) have exhibited exceptional efficacy in modeling the complex heterogeneity in heterogeneous information networks (HINs). The critical adv…