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DropEdge: Towards Deep Graph Convolutional Networks on Node Classification
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====
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[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/dropedge-towards-deep-graph-convolutional/node-classification-on-cora-full-supervised)](https://paperswithcode.com/sota/node-classification-on-cora-full-supervised?p=dropedge-towards-deep-graph-convolutional)
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[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/dropedge-towards-deep-graph-convolutional/node-classification-on-citeseer-full)](https://paperswithcode.com/sota/node-classification-on-citeseer-full?p=dropedge-towards-deep-graph-convolutional)
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[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/dropedge-towards-deep-graph-convolutional/node-classification-on-pubmed-full-supervised)](https://paperswithcode.com/sota/node-classification-on-pubmed-full-supervised?p=dropedge-towards-deep-graph-convolutional)
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[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/dropedge-towards-deep-graph-convolutional/node-classification-on-reddit)](https://paperswithcode.com/sota/node-classification-on-reddit?p=dropedge-towards-deep-graph-convolutional)
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This is a Pytorch implementation of paper: DropEdge: Towards Deep Graph Convolutional Networks on Node Classification
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## Benchmark Results
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For the details of backbones in Tables, please refer to the Appendix B.2 in papers. All results are obtained on GPU (CUDA Version 9.0.176).
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For the details of backbones in Tables, please refer to the Appendix B.2 in the paper. All results are obtained on GPU (CUDA Version 9.0.176).
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### Full-supervised Setting Results
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The following table demonstrates the testing accuracy (%) comparisons on different backbones and layers w and w/o DropEdge.

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