60 citations · 84 across the 12 of their papers we have counts for
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cs.LG2022★ 8 cited
RAW-GNN: RAndom Walk Aggregation based Graph Neural Network
Di Jin, Rui Wang, Meng Ge +4
Graph-Convolution-based methods have been successfully applied to representation learning on homophily graphs where nodes with the same label or similar attributes tend to connect…
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.LG2021
Sketching as a Tool for Understanding and Accelerating Self-attention for Long Sequences
Yifan Chen, Qi Zeng, Dilek Hakkani-Tur +3
Transformer-based models are not efficient in processing long sequences due to the quadratic space and time complexity of the self-attention modules. To address this limitation, Li…