51 citations · 185 across the 18 of their papers we have counts for
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cs.LG2021
Block Modeling-Guided Graph Convolutional Neural Networks
Dongxiao He, Chundong Liang, Huixin Liu +3
Graph Convolutional Network (GCN) has shown remarkable potential of exploring graph representation. However, the GCN aggregating mechanism fails to generalize to networks with hete…
cs.LG2021★ 5 cited
Powerful Graph Convolutioal Networks with Adaptive Propagation Mechanism for Homophily and Heterophily
Tao Wang, Rui Wang, Di Jin +2
Graph Convolutional Networks (GCNs) have been widely applied in various fields due to their significant power on processing graph-structured data. Typical GCN and its variants work…
cs.CL2021★ 5 cited
HTCInfoMax: A Global Model for Hierarchical Text Classification via Information Maximization
Zhongfen Deng, Hao Peng, Dongxiao He +2
The current state-of-the-art model HiAGM for hierarchical text classification has two limitations. First, it correlates each text sample with all labels in the dataset which contai…