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Code for CIKM'18 paper, Linked Causal Variational Autoencoder for Inferring Paired Spillover Effects.
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README.md

CIKM18-Linked Causal Variational Autoencoder

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.

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