https://arxiv.org/abs/2005.00687
| Method | #params | test AP (%) |
|---|---|---|
| DeeperGCN-VN+FLAG | 5.6M | 28.42 |
| DGN | 6.7M | 28.85 |
| GINE-VN | 6.1M | 29.17 |
| PHC-GNN | 1.7M | 29.47 |
| GINE-APPNP | 6.1M | 29.79 |
| Graphormer | 119.5M | 31.39 |
| Method | #params | test AP (%) |
|---|---|---|
| GCN-GraphNorm | 526K | 78.83 |
| PNA | 326K | 79.05 |
| PHC-GNN | 111K | 79.34 |
| DeeperGCN-FLAG | 532K | 79.42 |
| DGN | 114K | 79.70 |
| Graphormer | 47.0M | 80.51 |
Prepare your pre-trained models following our paper "Do Transformers Really Perform Bad for Graph Representation?".
Fine-tuning your pre-trained model on OGBG-MolPCBA:
bash pcba.sh
Fine-tuning your pre-trained model on OGBG-MolHIV:
bash hiv.sh
Please kindly cite this paper if you use the code:
@article{ying2021transformers,
title={Do Transformers Really Perform Bad for Graph Representation?},
author={Ying, Chengxuan and Cai, Tianle and Luo, Shengjie and Zheng, Shuxin and Ke, Guolin and He, Di and Shen, Yanming and Liu, Tie-Yan},
journal={arXiv preprint arXiv:2106.05234},
year={2021}
}
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