| Title | Causal Inference |
| Authors | Kuang, Kun Li, Lian Geng, Zhi Xu, Lei Zhang, Kun Liao, Beishui Huang, Huaxin Ding, Peng Miao, Wang Jiang, Zhichao |
| Affiliation | Zhejiang Univ, Coll Comp Sci & Technol, Hangzhou 310058, Peoples R China Hefei Univ Technol, Dept Comp Sci & Technol, Hefei 230009, Peoples R China Peking Univ, Sch Math Sci, Beijing 100871, Peoples R China Shanghai Jiao Tong Univ, Dept Comp Sci & Engn, Shanghai 200240, Peoples R China Carnegie Mellon Univ, Dept Philosophy, Pittsburgh, PA 15213 USA Zhejiang Univ, Sch Humanities, Hangzhou 310058, Peoples R China Univ Calif Berkeley, Berkeley, CA 94720 USA Peking Univ, Guanghua Sch Management, Beijing 100871, Peoples R China Harvard Univ, Dept Govt, Cambridge, MA 02138 USA Harvard Univ, Dept Stat, Cambridge, MA 02138 USA |
| Keywords | EXACT CONFIDENCE-INTERVALS INSTRUMENTAL VARIABLES RANDOMIZATION INFERENCE REGRESSION ADJUSTMENTS COVARIATE BALANCE MISSING DATA RERANDOMIZATION INTERFERENCE TRIALS IDENTIFICATION |
| Issue Date | Mar-2020 |
| Publisher | ENGINEERING |
| Abstract | Causal inference is a powerful modeling tool for explanatory analysis, which might enable current machine learning to become explainable. How to marry causal inference with machine learning to develop explainable artificial intelligence (XAI) algorithms is one of key steps toward to the artificial intelligence 2.0. With the aim of bringing knowledge of causal inference to scholars of machine learning and artificial intelligence, we invited researchers working on causal inference to write this survey from different aspects of causal inference. This survey includes the following sections: ''Estimating average treatment effect: A brief review and beyond" from Dr. Kun Kuang, ''Attribution problems in counterfactual inference" from Prof. Lian Li, ''The Yule-Simpson paradox and the surrogate paradox" from Prof. Zhi Geng, ''Causal potential theory" from Prof. Lei Xu, ''Discovering causal information from observational data" from Prof. Kun Zhang, ''Formal argumentation in causal reasoning and explanation" from Profs. Beishui Liao and Huaxin Huang, ''Causal inference with complex experiments" from Prof. Peng Ding, ''Instrumental variables and negative controls for observational studies" from Prof. Wang Miao, and ''Causal inference with interference" from Dr. Zhichao Jiang. (C) 2020 THE AUTHORS. Published by Elsevier LTD on behalf of Chinese Academy of Engineering and Higher Education Press Limited Company. |
| URI | http://hdl.handle.net/20.500.11897/588888 |
| ISSN | 2095-8099 |
| DOI | 10.1016/j.eng.2019.08.016 |
| Indexed | SSCI Scopus EI |
| Appears in Collections: | 数学科学学院 光华管理学院 |
