wehub-resource-sync
26 lines
814 B
Markdown
26 lines
814 B
Markdown
Geometric Deep Learning models
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=========
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This example shows how to use geometric deep learning models defined in `dgl.nn.pytorch.conv` for
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graph classification.
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Currently we support following models:
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- [ChebNet](https://arxiv.org/pdf/1606.09375.pdf)
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- [MoNet](https://arxiv.org/pdf/1611.08402.pdf)
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## Image Classification on MNIST
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By transforming images to graphs, graph classifcation algorithms could
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be applied to image classification problems.
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### Usage
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```bash
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python mnist.py --model cheb --gpu 0
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python mnist.py --model monet --gpu 0
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```
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### Acknowledgement
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We thank [Xavier Bresson](https://github.com/xbresson) for providing
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code for graph coarsening algorithm and grid graph building in
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[CE7454_2019 Labs](https://github.com/xbresson/CE7454_2019/tree/master/codes/labs_lecture14/lab01_ChebGCNs).
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