6 papers
Contrastive Graph Condensation: Advancing Data Versatility through Self-Supervised Learning
Xinyi Gao, Yayong Li, Tong Chen +3
With the increasing computation of training graph neural networks (GNNs) on large-scale graphs, graph condensation (GC) has emerged as a promising solution to synthesize a compact,…
Epidemiology-informed Network for Robust Rumor Detection
Wei Jiang, Tong Chen, Xinyi Gao +3
The rapid spread of rumors on social media has posed significant challenges to maintaining public trust and information integrity. Since an information cascade process is essential…
Physics-guided Active Sample Reweighting for Urban Flow Prediction
Wei Jiang, Tong Chen, Guanhua Ye +4
Urban flow prediction is a spatio-temporal modeling task that estimates the throughput of transportation services like buses, taxis, and ride-sharing, where data-driven models have…
Graph Condensation for Open-World Graph Learning
Xinyi Gao, Tong Chen, Wentao Zhang +3
The burgeoning volume of graph data presents significant computational challenges in training graph neural networks (GNNs), critically impeding their efficiency in various applicat…
RobGC: Towards Robust Graph Condensation
Xinyi Gao, Hongzhi Yin, Tong Chen +3
Graph neural networks (GNNs) have attracted widespread attention for their impressive capability of graph representation learning. However, the increasing prevalence of large-scale…
Rethinking and Accelerating Graph Condensation: A Training-Free Approach with Class Partition
Xinyi Gao, Guanhua Ye, Tong Chen +3
The increasing prevalence of large-scale graphs poses a significant challenge for graph neural network training, attributed to their substantial computational requirements. In resp…