350 citations · 362 across the 4 of their papers we have counts for
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cs.LG2022★ 3 cited
Comprehensive Graph Gradual Pruning for Sparse Training in Graph Neural Networks
Chuang Liu, Xueqi Ma, Yibing Zhan +5
Graph Neural Networks (GNNs) tend to suffer from high computation costs due to the exponentially increasing scale of graph data and the number of model parameters, which restricts…
cs.LG2022★ 9 cited
Graph Pooling for Graph Neural Networks: Progress, Challenges, and Opportunities
Chuang Liu, Yibing Zhan, Jia Wu +5
Graph neural networks have emerged as a leading architecture for many graph-level tasks, such as graph classification and graph generation. As an essential component of the archite…