Papers › GIDN: A Lightweight Graph Inception Diffusion Network for High-efficient Link Prediction
GIDN: A Lightweight Graph Inception Diffusion Network for High-efficient Link Prediction
Zixiao Wang, Yuluo Guo, Jin Zhao, Yu Zhang, Hui Yu, Xiaofei Liao, Biao Wang, Ting Yu
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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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Link Property Prediction | ogbl-collab | GIDN@YITU | Ext. data | No | #3 of 34 | Archive leaderboard | report |
| Link Property Prediction | ogbl-collab | GIDN@YITU | Number of params | 60449025 | #3 of 34 | Archive leaderboard | report |
| Link Property Prediction | ogbl-collab | GIDN@YITU | Test Hits@50 | 0.7096 ± 0.0055 | #3 of 34 | Archive leaderboard | report |
| Link Property Prediction | ogbl-collab | GIDN@YITU | Validation Hits@50 | 0.9620 ± 0.0040 | #3 of 34 | Archive leaderboard | report |
| Link Property Prediction | ogbl-ddi | GIDN@YITU | Ext. data | No | #4 of 31 | Archive leaderboard | report |
| Link Property Prediction | ogbl-ddi | GIDN@YITU | Number of params | 3506691 | #4 of 31 | Archive leaderboard | report |
| Link Property Prediction | ogbl-ddi | GIDN@YITU | Test Hits@20 | 0.9542 ± 0.0000 | #4 of 31 | Archive leaderboard | report |
| Link Property Prediction | ogbl-ddi | GIDN@YITU | Validation Hits@20 | 0.8258 ± 0.0000 | #4 of 31 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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