3 papers
cs.LG2024
Heterophilous Distribution Propagation for Graph Neural Networks
Zhuonan Zheng, Sheng Zhou, Hongjia Xu +6
Graph Neural Networks (GNNs) have achieved remarkable success in various graph mining tasks by aggregating information from neighborhoods for representation learning. The success r…
cs.LG2024
Revisiting the Message Passing in Heterophilous Graph Neural Networks
Zhuonan Zheng, Yuanchen Bei, Sheng Zhou +6
Graph Neural Networks (GNNs) have demonstrated strong performance in graph mining tasks due to their message-passing mechanism, which is aligned with the homophily assumption that…
cs.LG2024
A Survey on Graph Condensation
Hongjia Xu, Liangliang Zhang, Yao Ma +3
Analytics on large-scale graphs have posed significant challenges to computational efficiency and resource requirements. Recently, Graph condensation (GC) has emerged as a solution…