11 citations · 15 across the 3 of their papers we have counts for
3 papers
cs.SI2023★ 11 cited
Finding the Missing-half: Graph Complementary Learning for Homophily-prone and Heterophily-prone Graphs
Yizhen Zheng, He Zhang, Vincent CS Lee +3
Real-world graphs generally have only one kind of tendency in their connections. These connections are either homophily-prone or heterophily-prone. While graphs with homophily-pron…
cs.LG2022★ 3 cited
Unifying Graph Contrastive Learning with Flexible Contextual Scopes
Yizhen Zheng, Yu Zheng, Xiaofei Zhou +3
Graph contrastive learning (GCL) has recently emerged as an effective learning paradigm to alleviate the reliance on labelling information for graph representation learning. The co…
cs.LG2022★ 1 cited
Towards Unsupervised Deep Graph Structure Learning
Yixin Liu, Yu Zheng, Daokun Zhang +3
In recent years, graph neural networks (GNNs) have emerged as a successful tool in a variety of graph-related applications. However, the performance of GNNs can be deteriorated whe…