TBD.
Léon Bottou, From Causal Graphs to Causal Invariance
For many problems, it’s difficult to even attempt drawing a causal graph. While structural causal models provide a complete framework for causal inference, it is often hard to encode known physical laws (such as Newton’s gravitation, or the ideal gas law) as causal graphs. In familiar machine learning territory, how does one model the causal relationships between individual pixels and a target prediction? This is one of the motivating questions behind the paper Invariant Risk Minimization (IRM). In place of structured graphs, the authors elevate invariance to the defining feature of causality.
Nisha Muktewar and Chris Wallace, Causality for Machine Learning is the book Bottou recommends on this theme.
References
Arjovsky, Martin, Léon Bottou, Ishaan Gulrajani, and David Lopez-Paz. 2020. “Invariant Risk Minimization.” March 27, 2020. http://arxiv.org/abs/1907.02893.
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Friedrich, Sarah, Gerd Antes, Sigrid Behr, Harald Binder, Werner Brannath, Florian Dumpert, Katja Ickstadt, et al. 2020. “Is There a Role for Statistics in Artificial Intelligence?” September 13, 2020. http://arxiv.org/abs/2009.09070.
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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.
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Schölkopf, Bernhard, Francesco Locatello, Stefan Bauer, Nan Rosemary Ke, Nal Kalchbrenner, Anirudh Goyal, and Yoshua Bengio. 2021. “Towards Causal Representation Learning.” February 22, 2021. http://arxiv.org/abs/2102.11107.
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.
Zhang, Kun, Mingming Gong, Petar Stojanov, Biwei Huang, Qingsong Liu, and Clark Glymour. 2020. “Domain Adaptation as a Problem of Inference on Graphical Models.” In Advances in Neural Information Processing Systems. Vol. 33. https://arxiv.org/abs/2002.03278.
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