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GIDN: A Lightweight Graph Inception Diffusion Network for High-efficient Link Prediction

4 October 2022
Zixiao Wang
Yuluo Guo
Jin Zhao
Yu Zhang
Hui Yu
Xiaofei Liao
Biao Wang
Ting Yu
    DiffM
    GNN
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Abstract

In this paper, we propose a Graph Inception Diffusion Networks(GIDN) model. This model generalizes graph diffusion in different feature spaces, and uses the inception module to avoid the large amount of computations caused by complex network structures. We evaluate GIDN model on Open Graph Benchmark(OGB) datasets, reached an 11% higher performance than AGDN on ogbl-collab dataset.

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