Code for research paper:
Linked Causal Variational Autoencoder for Inferring Paired Spillover Effects.
Please cite us via this bibtex if you use this code for further development or as a baseline method in your work:
@inproceedings{rakesh2018linked,
title={Linked Causal Variational Autoencoder for Inferring Paired Spillover Effects},
author={Rakesh, Vineeth and Guo, Ruocheng and Moraffah, Raha and Agarwal, Nitin and Liu, Huan},
booktitle={Proceedings of the 27th ACM International Conference on Information and Knowledge Management},
pages={1679--1682},
year={2018},
organization={ACM}
}
In this work, we consider spill-over effect between instances for learning causal effects from data.
Acknowledgement: The code is developed based on the code released by authors of the NIPS 2017 paper:
Louizos, Christos, Uri Shalit, Joris M. Mooij, David Sontag, Richard Zemel, and Max Welling. "Causal effect inference with deep latent-variable models." In Advances in Neural Information Processing Systems, pp. 6446-6456. 2017.
For the Amazon dataset we processed and used for the paper, please check out: Download Amazon Dataset Here
For the job training dataset, please refer to the paper.
Feel free to email me rguo12 at asu dot edu for any question and collaboration.