38 citations · 163 across the 25 of their papers we have counts for
Showing 2023 · cs.LGShow all
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cs.LG2023★ 10 cited
Resurrecting Label Propagation for Graphs with Heterophily and Label Noise
Yao Cheng, Caihua Shan, Yifei Shen +3
Label noise is a common challenge in large datasets, as it can significantly degrade the generalization ability of deep neural networks. Most existing studies focus on noisy labels…
cs.LG2023★ 3 cited
SIGMA: An Efficient Heterophilous Graph Neural Network with Fast Global Aggregation
Haoyu Liu, Ningyi Liao, Siqiang Luo
Graph neural networks (GNNs) realize great success in graph learning but suffer from performance loss when meeting heterophily, i.e. neighboring nodes are dissimilar, due to their…