dmlc--dgl
Chang Liu
885be1784b
* Refactor GCN example * Refactor GCN based on graphsage * Readme update * Minor update * update * Remove user-defined GCN implementation * README update * Update * Update CONTRIBUTORS.md * update task_example_test Co-authored-by: Xin Yao <xiny@nvidia.com>
23 行
503 B
Markdown
23 行
503 B
Markdown
Graph Convolutional Networks (GCN)
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============
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- Paper link: [https://arxiv.org/abs/1609.02907](https://arxiv.org/abs/1609.02907)
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- Author's code repo: [https://github.com/tkipf/gcn](https://github.com/tkipf/gcn).
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How to run
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-------
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### DGL built-in GraphConv module
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Run with the following (available dataset: "cora", "citeseer", "pubmed")
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```bash
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python3 train.py --dataset cora
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```
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Summary
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-------
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* cora: ~0.810 (paper: 0.815)
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* citeseer: ~0.707 (paper: 0.703)
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* pubmed: ~0.792 (paper: 0.790)
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