718 citations · 976 across the 5 of their papers we have counts for
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cs.LG2021★ 222 cited
DGL-LifeSci: An Open-Source Toolkit for Deep Learning on Graphs in Life Science
Mufei Li, Jinjing Zhou, Jiajing Hu +4
Graph neural networks (GNNs) constitute a class of deep learning methods for graph data. They have wide applications in chemistry and biology, such as molecular property prediction…
cs.LG2021★ 13 cited
Graph Neural Networks Inspired by Classical Iterative Algorithms
Yongyi Yang, Tang Liu, Yangkun Wang +6
Despite the recent success of graph neural networks (GNN), common architectures often exhibit significant limitations, including sensitivity to oversmoothing, long-range dependenci…