This is a PyTorch implementation of the IAGNN model from paper [Interaction-Aware Graph Neural Networks for Fault Diagnosis of Complex Industrial Processes](DOI: 10.1109/TNNLS.2021.3132376)
- Python 3.7
- Pytorch 1.7.0+cu110
- torch-cluster 1.5.8
- torch-geometric 1.6.1
- torch-scatter 2.0.5
- torch-sparse 0.6.8
- torch-geometric >= 1.6.0
- HGP-SL
- sparse-softmax
If you find IAGNN useful for your research, please citing the following paper:
@ARTICLE{9655479, author={Chen, Dongyue and Liu, Ruonan and Hu, Qinghua and Ding, Steven X.}, journal={IEEE Transactions on Neural Networks and Learning Systems}, title={Interaction-Aware Graph Neural Networks for Fault Diagnosis of Complex Industrial Processes}, year={2021}, volume={}, number={}, pages={1-14}, doi={10.1109/TNNLS.2021.3132376}}