Guarding Against Adversarial Domain Shifts with Counterfactual Regularization

By Christina Heinze-Deml, Nicolai Meinshausen. 2017

9 citations recorded by the source corpus.

How researchers see this paper

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1. Percy Liang
2. Pang Wei Koh
3. Shiori Sagawa
4. Tatsunori B. Hashimoto
5. Yoshua Bengio
6. Sergey Levine
7. Mohit Bansal
8. Quoc V. Le

Citations in the corpus

• Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization (2019, background): “…prediction models, mostly from the causal inference literature, similarly aim to achieve high performance on a range of test distributions (Peters et al., 2016; B¨uhlmann & Meinshausen, 2016; Heinze-Deml & Meinshausen, 2017; Rothenh¨ausler et al., 2018; Yang et al., 2019; Arjovsky et al., 2019).”