This is the code for the paper "Missing Data Imputation with Uncertainty-Driven Network" which is accepted by SIGMOD 2024.
.
├── data # dataset files
├── baselines # the baselines of GAIN, VGAIN and TDM
├── mechanism.py # the missing mechanism
├── nngp.py # the neural network gaussian process
├── data_loader.py # data loader
├── utils.py # some help functions
├── main_hnsw_fast.py # the overall entrance
├── downstream_classification.py # the downstream classification using SVM
└── README.md
bash run_MCAR.sh
bash run_MAR.sh
bash run_MNAR.sh
@article{wang2024uncertainty,
title={Missing Data Imputation with Uncertainty-Driven Network},
author={Wang, Jianwei and Zhang, Ying and Wang, Kai and Lin, Xuemin and Zhang, Wenjie},
journal={Proceedings of the ACM on Management of Data},
volume={2},
number={3},
pages={1--25},
year={2024},
publisher={ACM New York, NY, USA}
}