CunWang520 / RGLT

GLT has presented the first attempt to accelerate GNN inference. Though promising, GLT encounters robustness and generalization issues when deployed in real-world scenarios. To tackle these issues, we propose the Resilient Graph Lottery Ticket (RGLT) to find more robust and generalizable GLT in GNNs.

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RGLT

GLT has presented the first attempt to accelerate GNN inference. Though promising, GLT encounters robustness and generalization issues when deployed in real-world scenarios. To tackle these issues, we propose the Resilient Graph Lottery Ticket (RGLT) to find more robust and generalizable GLT in GNNs.

The motivation of reactivation strategy

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The overview of RGLT

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Results

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Reference

If you find this work useful, please cite it as:

@article{wang2023brave, title={Brave the wind and the waves: Discovering robust and generalizable graph lottery tickets}, author={Wang, Kun and Liang, Yuxuan and Li, Xinglin and Li, Guohao and Ghanem, Bernard and Zimmermann, Roger and Yi, Huahui and Zhang, Yudong and Wang, Yang and others}, journal={IEEE Transactions on Pattern Analysis and Machine Intelligence}, year={2023}, publisher={IEEE} }

About

GLT has presented the first attempt to accelerate GNN inference. Though promising, GLT encounters robustness and generalization issues when deployed in real-world scenarios. To tackle these issues, we propose the Resilient Graph Lottery Ticket (RGLT) to find more robust and generalizable GLT in GNNs.


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Language:Python 100.0%