Causal inference in deep neural nets


TBD.

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Ng, Ignavier, Zhuangyan Fang, Shengyu Zhu, Zhitang Chen, and Jun Wang. 2020. “Masked Gradient-Based Causal Structure Learning.” February 17, 2020. http://arxiv.org/abs/1910.08527.

Ng, Ignavier, Shengyu Zhu, Zhitang Chen, and Zhuangyan Fang. 2019. “A Graph Autoencoder Approach to Causal Structure Learning.” In Advances in Neural Information Processing Systems. http://arxiv.org/abs/1911.07420.

Rakesh, Vineeth, Ruocheng Guo, Raha Moraffah, Nitin Agarwal, and Huan Liu. 2018. “Linked Causal Variational Autoencoder for Inferring Paired Spillover Effects.” In Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 1679–82. CIKM ’18. New York, NY, USA: Association for Computing Machinery. https://doi.org/10.1145/3269206.3269267.

Rotnitzky, Andrea, and Ezequiel Smucler. 2020. “Efficient Adjustment Sets for Population Average Causal Treatment Effect Estimation in Graphical Models.” Journal of Machine Learning Research 21 (188): 1–86. http://jmlr.org/papers/v21/19-1026.html.

Yang, Mengyue, Furui Liu, Zhitang Chen, Xinwei Shen, Jianye Hao, and Jun Wang. 2020. “CausalVAE: Disentangled Representation Learning via Neural Structural Causal Models.” July 1, 2020. http://arxiv.org/abs/2004.08697.