Reinforced Causal Explainer for Graph Neural Networks

PyTorch implementation for Reinforced Causal Explainer for Graph Neural Networks

Xiang Wang, Yingxin Wu, An Zhang, Fuli Feng, Xiangnan He and Tat-Seng Chua

In TPAMI.

Dependencies & Dataset

To reproduce the results in our paper, simply run

bash running_mutag.sh

bash running_vg.sh

bash running_reddit5k.sh

Hyper-parameter settings are shown below:

Name		Name	Last commit message	Last commit date
Latest commit History 5 Commits
.idea		.idea
Data		Data
explainer_output		explainer_output
explainer_params		explainer_params
log		log
module		module
params		params
star		star
.DS_Store		.DS_Store
Hyperparameters.png		Hyperparameters.png
README.md		README.md
environment.yml		environment.yml
final_run.py		final_run.py
rc_explainer_pool.py		rc_explainer_pool.py
run_ba3.py		run_ba3.py
run_ba3_pro.py		run_ba3_pro.py
run_ba3_star.py		run_ba3_star.py
run_mutag.py		run_mutag.py
run_mutag_pro.py		run_mutag_pro.py
run_vg.py		run_vg.py
running_ba3.sh		running_ba3.sh
running_mutag.sh		running_mutag.sh
running_reddit5k.sh		running_reddit5k.sh
running_vg.sh		running_vg.sh
train_test_pool_batch.py		train_test_pool_batch.py
train_test_pool_batch2.py		train_test_pool_batch2.py
train_test_pool_batch3.py		train_test_pool_batch3.py