27 citations · 58 across the 9 of their papers we have counts for
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cs.LG2022★ 17 cited
Revisiting Graph Contrastive Learning from the Perspective of Graph Spectrum
Nian Liu, Xiao Wang, Deyu Bo +2
Graph Contrastive Learning (GCL), learning the node representations by augmenting graphs, has attracted considerable attentions. Despite the proliferation of various graph augmenta…
cs.LG2022★ 3 cited
Debiased Graph Neural Networks with Agnostic Label Selection Bias
Shaohua Fan, Xiao Wang, Chuan Shi +3
Most existing Graph Neural Networks (GNNs) are proposed without considering the selection bias in data, i.e., the inconsistent distribution between the training set with test set.…
cs.LG2022
Compact Graph Structure Learning via Mutual Information Compression
Nian Liu, Xiao Wang, Lingfei Wu +3
Graph Structure Learning (GSL) recently has attracted considerable attentions in its capacity of optimizing graph structure as well as learning suitable parameters of Graph Neural…