A PyTorch implementation of "[ANOMIX: A Simple yet Effective Graph Mixing Approach for GAD]"
Dependencies for all experiments of ANOMIX are as follows:
• Python == 3.7.8
• PyTorch == 1.6.0
• NetworkX == 2.6.3
• Scikit-learn == 0.23.2
• NumPy == 1.18.5
• SciPy == 1.7.3
• DGL == 0.4.1
All of datasets used in this paper are put in ./dataset folder and graph information (e.g., adjacency, attribute, and label) is included in each dataset file (.mat).
python run.py --dataset cora