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PyTorch implementation for 'GiGaMA: Generalizable Graph Masked Autoencoder via Collaborative Latent Space Reconstruction'

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GiGaMAE

This repository hosts the code for our CIKM'23 long paper 'GiGaMAE: Generalizable Graph Masked Autoencoder via Collaborative Latent Space Reconstruction.' by Yucheng Shi, Yushun Dong, Qiaoyu Tan, Jundong Li, and Ninghao Liu.

Dependencies

  • torch 1.12.0+cu116
  • torch-cluster 1.6.0
  • torch-geometric 2.1.0
  • torch-scatter 2.0.9
  • torch-sparse 0.6.15

If you have trouble in installing torch-geometric, you may find help in its official website.

Training & Evaluation

Node Classification and Clustering

sh run.sh

Link Prediction

sh run_lp.sh

Acknowledgements

Parts of implementation are reference to GRACE

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PyTorch implementation for 'GiGaMA: Generalizable Graph Masked Autoencoder via Collaborative Latent Space Reconstruction'

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