2 citations · 3 across the 2 of their papers we have counts for
2 papers
cs.LG2022★ 2 cited
Universal Deep GNNs: Rethinking Residual Connection in GNNs from a Path Decomposition Perspective for Preventing the Over-smoothing
Jie Chen, Weiqi Liu, Zhizhong Huang +3
The performance of GNNs degrades as they become deeper due to the over-smoothing. Among all the attempts to prevent over-smoothing, residual connection is one of the promising meth…
cs.LG2022★ 1 cited
Memory-based Message Passing: Decoupling the Message for Propogation from Discrimination
Jie Chen, Weiqi Liu, Jian Pu
Message passing is a fundamental procedure for graph neural networks in the field of graph representation learning. Based on the homophily assumption, the current message passing a…