Name		Name	Last commit message	Last commit date
.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

Repository files navigation

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

Please refer to environment.yml for environment setup and https://drive.google.com/file/d/1Cv2PBj4Tqcx-FzSO_wdQSletIxwof0IZ/view?usp=sharing to download dataset.

Reproductivity

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:

About

Reinforced Causal Explainer for Graph Neural Networks, TPAMI2022

causal-screening explainer gnn-explainer graph-neural-networks post-hoc-explanation reinforcement-learning-agent tpami2022

42 stars

2 watching

Report repository

Releases

Packages

Contributors

Languages