11 citations · 11 across the 5 of their papers we have counts for
6 papers
Towards Pre-trained Graph Condensation via Optimal Transport
Yeyu Yan, Shuai Zheng, Wenjun Hui +5
Graph condensation (GC) aims to distill the original graph into a small-scale graph, mitigating redundancy and accelerating GNN training. However, conventional GC approaches heavil…
Dynamic Graph Condensation
Dong Chen, Shuai Zheng, Yeyu Yan +4
Recent research on deep graph learning has shifted from static to dynamic graphs, motivated by the evolving behaviors observed in complex real-world systems. However, the temporal…
FlexCare: Leveraging Cross-Task Synergy for Flexible Multimodal Healthcare Prediction
Muhao Xu, Zhenfeng Zhu, Youru Li +4
Multimodal electronic health record (EHR) data can offer a holistic assessment of a patient's health status, supporting various predictive healthcare tasks. Recently, several studi…
SiGNN: A Spike-induced Graph Neural Network for Dynamic Graph Representation Learning
Dong Chen, Shuai Zheng, Muhao Xu +2
In the domain of dynamic graph representation learning (DGRL), the efficient and comprehensive capture of temporal evolution within real-world networks is crucial. Spiking Neural N…
Unleashing the potential of GNNs via Bi-directional Knowledge Transfer
Shuai Zheng, Zhizhe Liu, Zhenfeng Zhu +3
Based on the message-passing paradigm, there has been an amount of research proposing diverse and impressive feature propagation mechanisms to improve the performance of GNNs. Howe…
Node-oriented Spectral Filtering for Graph Neural Networks
Shuai Zheng, Zhenfeng Zhu, Zhizhe Liu +2
Graph neural networks (GNNs) have shown remarkable performance on homophilic graph data while being far less impressive when handling non-homophilic graph data due to the inherent…