40 citations · 82 across the 11 of their papers we have counts for
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cs.LG2022★ 13 cited
JuryGCN: Quantifying Jackknife Uncertainty on Graph Convolutional Networks
Jian Kang, Qinghai Zhou, Hanghang Tong
Graph Convolutional Network (GCN) has exhibited strong empirical performance in many real-world applications. The vast majority of existing works on GCN primarily focus on the accu…
cs.LG2022★ 40 cited
RawlsGCN: Towards Rawlsian Difference Principle on Graph Convolutional Network
Jian Kang, Yan Zhu, Yinglong Xia +2
Graph Convolutional Network (GCN) plays pivotal roles in many real-world applications. Despite the successes of GCN deployment, GCN often exhibits performance disparity with respec…