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Qiuliang Zhang

2 accepted papers

2023

Self-supervised Graph Neural Networks via Low-Rank Decomposition

NeurIPS 2023poster

Self-supervised learning is introduced to train graph neural networks (GNNs) by employing propagation-based GNNs designed for semi-supervised learning tasks. Unfortunately, this common choice tends to cause two serious issues. Firstly, global parameters cause the model lack the ability to capture th…

Cited by 14SourcePDFScholar
2022

OPEN: Orthogonal Propagation with Ego-Network Modeling

NeurIPS 2022accept

To alleviate the unfavorable effect of noisy topology in Graph Neural networks (GNNs), some efforts perform the local topology refinement through the pairwise propagation weight learning and the multi-channel extension. Unfortunately, most of them suffer a common and fatal drawback: irrelevant propa…

Cited by 7SourcePDFScholar