Data-Free Adversarial Knowledge Distillation for Graph Neural Networks Paper link: https://arxiv.org/pdf/2205.03811 Author's code repo: https://anonymous.4open.science/r/DF-GNNs-EC75 Dataset Statics Dataset # Graphs # Nodes # Edges # Features # Classes MUTAG 188 ~17.9 ~39.6 7 2 Refer to TUDataset. Results TL_BACKEND="torch" python train_teacher.py --dataset MUTAG TL_BACKEND="torch" python train_student.py --dataset MUTAG --student gcn TL_BACKEND="torch" python train_student.py --dataset MUTAG --student gin Dataset Student Model Paper Our(th) MUTAG gcn 76.2% 88.2% MUTAG gin 90.8% 88.2% MUTAG gat 79.5% 88.2% MUTAG graphsage 79.1% 88.2%