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Official Repository of "A Fair Comparison of Graph Neural Networks for Graph Classification", ICLR 2020
| Date | Stars |
|---|---|
| 2026-07-31 | 401 |
| 2026-08-05 | 401 |
| 2026-08-06 | 401 |
| 2026-08-14 | 401 |
| 2026-08-15 | 401 |
| 2026-08-18 | 401 |
| 2026-09-20 | 401 |
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# A Fair Comparison of Graph Neural Networks for Graph Classification (ICLR 2020)
## Summary
The library includes data and scripts to reproduce the experiments reported in the paper.
#### If you happen to use or modify this code, please remember to cite our paper:
[Federico Errica, Marco Podda, Davide Bacciu, Alessio Micheli: *A Fair Comparison of Graph Neural Networks for Graph Classification*](https://openreview.net/pdf?id=HygDF6NFPB). *Proceedings of the 8th International Conference on Learning Representations (ICLR 2020).*
@inproceedings{errica_fair_2020,
title = {A fair comparison of graph neural networks for graph classification},
booktitle = {Proceedings of the 8th {International} {Conference} on {Learning} {Representations} ({ICLR})},
author = {Errica, Federico and Podda, Marco and Bacciu, Davide and Micheli, Alessio},
year = {2020}
}
--
## Updated Table with Results (CHEMICAL)
| | D\&D | NCI1 | PROTEINS |
|-----------------------------|-------------------------|--------------------------|--------------------------|
| Baseline | $\mathbf{78.4}\pm 4.5 $ | $69.8 \pm 2.2 $ | $\mathbf{75.8} \pm 3.7 $ |
| DGCNN | $76.6 \pm 4.3 $ | $76.4 \pm 1.7 $ | $72.9 \pm 3.5 $ |
| DiffPool | $75.0 \pm 3.5 $ | $76.9 \pm 1.9 $ | $73.7 \pm 3.5 $ |
| ECC | $72.6 \pm 4.1 $ | $76.2 \pm 1.4 $ | $72.3 \pm 3.4 $ |
| GIN | $75.3 \pm 2.9 $ | $\mathbf{80.0} \pm 1.4 $ | $73.3 \pm 4.0 $ |
| GraphSAGE | $72.9 \pm 2.0 $ | $76.0 \pm 1.8 $ | $73.0 \pm 4.5 $ |
| [CGMM](https://www.jmlr.org/papers/volume21/19-470/19-470.pdf) | $74.9 \pm 3.4 $ | $76.2 \pm 2.0$ | $74.0 \pm 3.9$ |
| [ECGMM](https://ieeexplore.ieee.org/document/9533430/) | $73.9 \pm4.1$ | $78.5 \pm 1.7$ | $73.3 \pm 4.1$ |
| [iCGMM<sub>*f*</sub>](https://proceedings.mlr.press/v162/castellana22a/castellana22a.pdf) | $75.1 \pm 3.8$ | $76.4 \pm1.4$ | $73.2 \pm 3.9$ |
| [GSPN](https://arxiv.org/pdf/2305.10544.pdf) | - | $76.6 \pm 1.9$ | - |
## Updated Table with Results (SOCIAL + degree)
| | IMDB-B | IMDB-M | REDDIT-B | REDDIT-5K | COLLAB |
|-----------------------------|-------------------------|--------------------------|-------------------------|--------------------------|-------------------------|
| Baseline | $70.8 \pm 5.0 $ | $\mathbf{49.1} \pm 3.5 $ | $82.2 \pm 3.0 $ | $52.2 \pm 1.5 $ | $70.2 \pm 1.5 $ |
| DGCNN | $69.2 \pm 3.0 $ | $45.6 \pm 3.4 $ | $87.8 \pm 2.5 $ | $49.2 \pm 1.2 $ | $71.2 \pm 1.9 $ |
| DiffPool | $68.4 \pm 3.3 $ | $45.6 \pm 3.4 $ | $89.1 \pm 1.6 $ | $53.8 \pm 1.4 $ | $68.9 \pm 2.0 $ |
| ECC | $67.7 \pm 2.8 $ | $43.5 \pm 3.1 $ | - | - | - |
| GIN | $71.2 \pm 3.9 $ | $48.5 \pm 3.3 $ | $89.9 \pm 1.9 $ | $\mathbf{56.1} \pm 1.7 $ | $75.6 \pm 2.3 $ |
| GraphSAGE | $68.8 \pm 4.5 $ | $47.6 \pm 3.5 $ | $84.3 \pm 1.9 $ | $50.0 \pm 1.3 $ | $73.9 \pm 1.7 $ |
| [CGMM](https://www.jmlr.org/papers/volume21/19-470/19-470.pdf) | $\mathbf{72.7} \pm 3.6$ | $47.5 \pm 3.9$ | $88.1 \pm 1.9$ | $52.4 \pm 2.2$ | $77.32 \pm 2.2$ |
| [ECGMM](https://ieeexplore.ieee.org/document/9533430/) | $70.7 \pmExcerpt of 8,016 characters
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matched fp:9d634f29946d30a8, llm:Repository title and description: 'Official Repository of "A Fair Comparison of Graph Neural Networks for Graph Classification", ICLR 2020' — implements and compares graph neural networks for graph classification tasks.
matched fp:9d634f29946d30a8, llm:Repository title and description: 'Official Repository of "A Fair Comparison of Graph Neural Networks for Graph Classification", ICLR 2020' — implements and compares graph neural networks for graph classification tasks.