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Mengzhe Li

2 accepted papers

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
2021

Diverse Message Passing for Attribute with Heterophily

NeurIPS 2021poster

Most of the existing GNNs can be modeled via the Uniform Message Passing framework. This framework considers all the attributes of each node in its entirety, shares the uniform propagation weights along each edge, and focuses on the uniform weight learning. The design of this framework possesses tw…

Cited by 83SourcePDFScholar