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Pytorch implementation of "Two Trades is not Baffled: Condensing Graph via Crafting Rational Gradient Matching"

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CTRL

Pytorch implementation of "Two Trades is not Baffled: Condensing Graph via Crafting Rational Gradient Matching".

ctrl

Run the code

For example, to get the condensed graph, run the following command:

python train_ctrl_induct.py --dataset reddit --sgc=1 --nlayers=2 --lr_feat=0.1  \ 
--lr_adj=0.1  --r=0.001 --seed=1 --gpu_id=0 --epochs=1000  --inner=1 --outer=10 --save=0 --alpha=0 --beta=0.2 --init_way=K-means

Requirements

Please see environment.

Run the following command to install:

conda env create -f environment.yaml

Acknowledgement

Our code is built upon GCond

Cite

If you find this repo to be useful, please cite our paper.

@misc{zhang2024trades,
      title={Two Trades is not Baffled: Condensing Graph via Crafting Rational Gradient Matching}, 
      author={Tianle Zhang and Yuchen Zhang and Kun Wang and Kai Wang and Beining Yang and Kaipeng Zhang and Wenqi Shao and Ping Liu and Joey Tianyi Zhou and Yang You},
      year={2024},
      eprint={2402.04924},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}

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Pytorch implementation of "Two Trades is not Baffled: Condensing Graph via Crafting Rational Gradient Matching"

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