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This is the code for the ICLR 2024 paper of ConsisGAD: Consistency Training with Learnable Data Augmentation for Graph Anomaly Detection with Limited Supervision..

This repository uses DGL to load graphs. The data needs to be converted to a format acceptable to the DGL

For example, when your data is in CSV format, see the guidance in https://docs.dgl.ai/en/0.8.x/guide/data-loadcsv.html.

Then, write your dataloader in ./modules/data_loader.py.

The configuration file should be put in the ./config directory.

Then, run

chmod +x scripts/run_baseline.sh
cd scripts && ./run_baseline.sh

The results should be stored at the ./results directory.