- Lu Zhang, Yongkai Wu, Xintao Wu: On Discrimination Discovery Using Causal Networks. SBP-BRiMS 2016.
- Lu Zhang, Yongkai Wu, Xintao Wu: Situation Testing-Based Discrimination Discovery: A Causal Inference Approach in IJCAI 2016.
- Francesco Bonchi, Sara Hajian, Bud Mishra, Daniele Ramazzotti: Exposing the Probabilistic Causal Structure of Discrimination. JDSA 3, 1-21 (2017).
- Lu Zhang, Xintao Wu: Anti-Discrimination Learning: A Causal Modeling-Based Framework. JDSA 4, 1-16(2017). survey
- Lu Zhang, Yongkai Wu, Xintao Wu: Achieving Non-Discrimination in Data Release. KDD 2017.
- Lu Zhang, Yongkai Wu, Xintao Wu: A Causal Framework for Discovering and Removing Direct and Indirect Discrimination. IJCAI 2017.
- Niki Kilbertus, Mateo Rojas Carulla, Giambattista Parascandolo, Moritz Hardt, Dominik Janzing, Bernhard Schölkopf: Avoiding Discrimination through Causal Reasoning. NIPS 2017.
- Matt J. Kusner, Joshua Loftus, Chris Russell, Ricardo Silva: Counterfactual Fairness. NIPS 2017.
- Chris Russell, Matt J. Kusner, Joshua Loftus, Ricardo Silva: When Worlds Collide: Integrating Different Counterfactual Assumptions in Fairness. NIPS 2017.
- Jiuyong Li, Jixue Liu, Lin Liu, Thuc Duy Le, Saisai Ma, Yizhao Han: Discrimination Detection by Causal Effect Estimation. IEEE Big Data 2017.
- Razieh Nabi, Ilya Shpitser: Fair Inference on Outcomes. AAAI 2018.
- Junzhe Zhang, Elias Bareinboim: Fairness in Decision-Making - the Causal Explanation Formula. AAAI 2018.
- Chelsea Barabas, Madars Virza, Karthik Dinakar, Joichi Ito, Jonathan Zittrain: Interventions over Predictions: Reframing the Ethical Debate for Actuarial Risk Assessment. FAT 2018.
- Fabio Massimo Zennaro, Magdalena Ivanovska: Pooling of Causal Models under Counterfactual Fairness via Causal Judgement Aggregation. Preprint 2018.
- Joshua R. Loftus, Chris Russell, Matt J. Kusner, Ricardo Silva: Causal Reasoning for Algorithmic Fairness. Preprint 2018.
- Lu Zhang, Yongkai Wu, Xintao Wu: Achieving Non-Discrimination in Prediction. IJCAI 2018.
- Yongkai Wu, Lu Zhang, Xintao Wu: On Discrimination Discovery and Removal in Ranked Data Using Causal Graph. KDD 2018.
- Fabio Massimo Zennaro, Magdalena Ivanovska: Counterfactually Fair Prediction Using Multiple Causal Models. EUMAS 2018.
- Silvia Chiappa: Path-Specific Counterfactual Fairness. AAAI 2019.
- Aria Khademi, Sanghack Lee, David Foley, Vasant G. Honavar: Fairness in Algorithmic Decision Making: An Excursion Through the Lens of Causality. WWW 2019.
- Matt J. Kusner, Chris Russell, Joshua R. Loftus, Ricardo Silva: Making Decisions That Reduce Discriminatory Impacts. ICML 2019.
- Babak Salimi, Luke Rodriguez, Bill Howe, Dan Suciu: Interventional Fairness: Causal Database Repair for Algorithmic Fairness. SIGMOD 2019.
- Niki Kilbertus, Philip J. Ball, Matt J. Kusner, Adrian Weller, Ricardo Silva: The Sensitivity of Counterfactual Fairness to Unmeasured Confounding. UAI 2019.
- Depeng Xu, Yongkai Wu, Shuhan Yuan, Lu Zhang, Xintao Wu: Achieving Causal Fairness through Generative Adversarial Networks. IJCAI 2019.
- Yongkai Wu, Lu Zhang, Xintao Wu: Counterfactual Fairness: Unidentification, Bound and Algorithm. IJCAI 2019.
- Bilal Qureshi, Faisal Kamiran, Asim Karim, Salvatore Ruggieri, Dino Pedreschi: Causal Inference for Social Discrimination Reasoning. J. Intell. Inf. Syst. 54(2) 2020.
- Lu Zhang, Yongkai Wu, Xintao Wu: Causal Modeling-Based Discrimination Discovery and Removal: Criteria, Bounds, and Algorithms. TKDD 31 2019.
- Yongkai Wu, Lu Zhang, Xintao Wu, Hanghang Tong: PC-Fairness: A Unified Framework for Measuring Causality-Based Fairness. NeurIPS 2019.
- Coston, Amanda; Mishler, Alan; Kennedy, Edward H.; Chouldechova, Alexandra: Counterfactual risk assessments, evaluation, and fairness
- Qureshi, Bilal; Kamiran, Faisal; Karim, Asim; Ruggieri, Salvatore; Pedreschi, Dino: Causal inference for social discrimination reasoning
- Huang, Wen; Wu, Yongkai; Zhang, Lu; Wu, Xintao: Fairness through equality of effort
- Ogura, Hikaru; Takeda, Akiko: Convex fairness constrained model using causal effect estimators
- Yang, Zekun; Feng, Juan: A causal inference method for reducing gender bias in word embedding relations
- Vig, Jesse; Gehrmann, Sebastian; Belinkov, Yonatan; Qian, Sharon; Nevo, Daniel; Singer, Yaron; Shieber, Stuart M.: Investigating gender bias in language models using causal mediation analysis
- Hu, Yaowei; Wu, Yongkai; Zhang, Lu; Wu, Xintao: Fair multiple decision making through soft interventions
- Chikahara, Yoichi; Sakaue, Shinsaku; Fujino, Akinori; Kashima, Hisashi: Learning individually fair classifier with path-specific causal-effect constraint