Web: http://arxiv.org/abs/2206.08181

June 17, 2022, 1:11 a.m. | Langzhang Liang, Zenglin Xu, Zixing Song, Irwin King, Jieping Ye

cs.LG updates on arXiv.org arxiv.org

Graph Neural Networks (GNNs) have attracted much attention due to their
ability in learning representations from graph-structured data. Despite the
successful applications of GNNs in many domains, the optimization of GNNs is
less well studied, and the performance on node classification heavily suffers
from the long-tailed node degree distribution. This paper focuses on improving
the performance of GNNs via normalization.

In detail, by studying the long-tailed distribution of node degrees in the
graph, we propose a novel normalization method for …

arxiv distribution graph graph neural networks lg networks neural neural networks

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