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Friedrich, Sarah, Gerd Antes, Sigrid Behr, Harald Binder, Werner Brannath, Florian Dumpert, Katja Ickstadt, et al. 2020. â€śIs There a Role for Statistics in Artificial Intelligence?â€ť September 13, 2020. http://arxiv.org/abs/2009.09070.

Kocaoglu, Murat, Christopher Snyder, Alexandros G. Dimakis, and Sriram Vishwanath. 2017. â€śCausalGAN: Learning Causal Implicit Generative Models with Adversarial Training.â€ť September 14, 2017. http://arxiv.org/abs/1709.02023.

Locatello, Francesco, Stefan Bauer, Mario Lucic, Gunnar RĂ¤tsch, Sylvain Gelly, Bernhard SchĂ¶lkopf, and Olivier Bachem. 2019. â€śChallenging Common Assumptions in the Unsupervised Learning of Disentangled Representations.â€ť June 18, 2019. http://arxiv.org/abs/1811.12359.

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

Ng, Ignavier, Shengyu Zhu, Zhitang Chen, and Zhuangyan Fang. 2019. â€śA Graph Autoencoder Approach to Causal Structure Learning.â€ť 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. â€śLinked Causal Variational Autoencoder for Inferring Paired Spillover Effects.â€ť In *Proceedings of the 27th ACM International Conference on Information and Knowledge Management*, 1679â€“82. CIKM â€™18. New York, NY, USA: Association for Computing Machinery. https://doi.org/10.1145/3269206.3269267.

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

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