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20212026
most citedMGDCF: Distance Learning via Markov Graph Diffusion for Neural Collaborative Filtering

69 citations · 113 across the 7 of their papers we have counts for

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Showing 2021 · cs.LGShow all

2 papers · 2 filters

cs.LG2021★ 1 cited

Contrastive Adaptive Propagation Graph Neural Networks for Efficient Graph Learning

Jun Hu, Shengsheng Qian, Quan Fang +1

Graph Neural Networks (GNNs) have achieved great success in processing graph data by extracting and propagating structure-aware features. Existing GNN research designs various prop…

cs.LG2021★ 9 cited

Efficient Graph Deep Learning in TensorFlow with tf_geometric

Jun Hu, Shengsheng Qian, Quan Fang +4

We introduce tf_geometric, an efficient and friendly library for graph deep learning, which is compatible with both TensorFlow 1.x and 2.x. tf_geometric provides kernel libraries f…