Semiparametric proximal causal inference

17 November 2020

E. T. Tchetgen Tchetgen

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Papers citing "Semiparametric proximal causal inference"

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Reinforcement Learning with Continuous Actions Under Unmeasured Confounding Yuhan Li Eugene Han Yifan Hu Wenzhuo Zhou Zhengling Qi Yifan Cui Ruoqing Zhu OffRL 53 0 0 01 May 2025
Detecting clinician implicit biases in diagnoses using proximal causal inference Kara Liu Russ Altman Vasilis Syrgkanis CML 40 0 0 27 Jan 2025
Controlling for Unobserved Confounding with Large Language Model Classification of Patient Smoking Status Samuel Lee Zach Wood-Doughty CML 38 0 0 05 Nov 2024
DNA-SE: Towards Deep Neural-Nets Assisted Semiparametric Estimation Qinshuo Liu Zixin Wang Xi-An Li Xinyao Ji Lei Zhang Lin Liu Zhonghua Liu 23 0 0 04 Aug 2024
REVEAL-IT: REinforcement learning with Visibility of Evolving Agent poLicy for InTerpretability Shuang Ao Simon Khan Haris Aziz Flora D. Salim 14 0 0 20 Jun 2024
Stochastic Optimization Algorithms for Instrumental Variable Regression with Streaming Data Xuxing Chen Abhishek Roy Yifan Hu Krishnakumar Balasubramanian 36 1 0 29 May 2024
Recovering Latent Confounders from High-dimensional Proxy Variables Nathan Mankovich Homer Durand Emiliano Díaz Gherardo Varando Gustau Camps-Valls 22 0 0 21 Mar 2024
Proxy Methods for Domain Adaptation Katherine Tsai Stephen R. Pfohl Olawale Salaudeen Nicole Chiou Matt J. Kusner Alexander DÁmour Oluwasanmi Koyejo Arthur Gretton OOD 24 2 0 12 Mar 2024
Regularized DeepIV with Model Selection Zihao Li Hui Lan Vasilis Syrgkanis Mengdi Wang Masatoshi Uehara 23 2 0 07 Mar 2024
Applied Causal Inference Powered by ML and AI Victor Chernozhukov Christian Hansen Nathan Kallus Martin Spindler Vasilis Syrgkanis CML 24 27 0 04 Mar 2024
AI in Pharma for Personalized Sequential Decision-Making: Methods, Applications and Opportunities Yuhan Li Hongtao Zhang Keaven M Anderson Songzi Li Ruoqing Zhu 9 0 0 30 Nov 2023
A Semiparametric Instrumented Difference-in-Differences Approach to Policy Learning Pan Zhao Yifan Cui CML 13 1 0 14 Oct 2023
The Blessings of Multiple Treatments and Outcomes in Treatment Effect Estimation Yong Wu Mingzhou Liu Jing Yan Yanwei Fu Shouyan Wang Yizhou Wang Xinwei Sun CML 8 0 0 29 Sep 2023
Doubly Robust Proximal Causal Learning for Continuous Treatments Yong Wu Yanwei Fu Shouyan Wang Xinwei Sun 21 1 0 22 Sep 2023
Forster-Warmuth Counterfactual Regression: A Unified Learning Approach Yachong Yang Arun K. Kuchibhotla E. T. Tchetgen 14 3 0 31 Jul 2023
Source Condition Double Robust Inference on Functionals of Inverse Problems Andrew Bennett Nathan Kallus Xiaojie Mao Whitney Newey Vasilis Syrgkanis Masatoshi Uehara 13 5 0 25 Jul 2023
Balanced Filtering via Disclosure-Controlled Proxies Siqi Deng Emily Diana Michael Kearns Aaron Roth 17 0 0 26 Jun 2023
Assumption-lean falsification tests of rate double-robustness of double-machine-learning estimators Lin Liu Rajarshi Mukherjee J. M. Robins 16 1 0 18 Jun 2023
A Cross-Moment Approach for Causal Effect Estimation Yaroslav Kivva Saber Salehkaleybar Negar Kiyavash CML 6 2 0 09 Jun 2023
Partial Identification of Causal Effects Using Proxy Variables AmirEmad Ghassami I. Shpitser E. T. Tchetgen CML 8 8 0 10 Apr 2023
A Unified Framework of Policy Learning for Contextual Bandit with Confounding Bias and Missing Observations Siyu Chen Yitan Wang Zhaoran Wang Zhuoran Yang OffRL 26 2 0 20 Mar 2023
Minimax Instrumental Variable Regression and $L_2$ Convergence Guarantees without Identification or Closedness Andrew Bennett Nathan Kallus Xiaojie Mao Whitney Newey Vasilis Syrgkanis Masatoshi Uehara 28 14 0 10 Feb 2023
Proximal Causal Learning of Conditional Average Treatment Effects Erik Sverdrup Yifan Cui CML 16 4 0 26 Jan 2023
Relaxing Instrument Exogeneity with Common Confounders Christian Tien CML 16 0 0 05 Jan 2023
An Instrumental Variable Approach to Confounded Off-Policy Evaluation Yang Xu Jin Zhu C. Shi S. Luo R. Song OffRL 6 12 0 29 Dec 2022
Optimal Treatment Regimes for Proximal Causal Learning Tao Shen Yifan Cui CML 18 3 0 19 Dec 2022
Estimating individual treatment effects under unobserved confounding using binary instruments Dennis Frauen Stefan Feuerriegel CML 14 17 0 17 Aug 2022
Inference on Strongly Identified Functionals of Weakly Identified Functions Andrew Bennett Nathan Kallus Xiaojie Mao Whitney Newey Vasilis Syrgkanis Masatoshi Uehara 25 15 0 17 Aug 2022
Proximal Survival Analysis to Handle Dependent Right Censoring Andrew Ying 6 7 0 15 Aug 2022
Bias Formulas for Violations of Proximal Identification Assumptions Raluca Cobzaru Roy Welsch Stan N. Finkelstein Kenney Ng Zach Shahn 14 2 0 29 Jul 2022
Future-Dependent Value-Based Off-Policy Evaluation in POMDPs Masatoshi Uehara Haruka Kiyohara Andrew Bennett Victor Chernozhukov Nan Jiang Nathan Kallus C. Shi Wen Sun OffRL 12 16 0 26 Jul 2022
Instrumented Common Confounding Christian Tien CML 11 2 0 26 Jun 2022
Provably Efficient Reinforcement Learning in Partially Observable Dynamical Systems Masatoshi Uehara Ayush Sekhari Jason D. Lee Nathan Kallus Wen Sun OffRL 47 31 0 24 Jun 2022
Pessimism in the Face of Confounders: Provably Efficient Offline Reinforcement Learning in Partially Observable Markov Decision Processes Miao Lu Yifei Min Zhaoran Wang Zhuoran Yang OffRL 38 22 0 26 May 2022
Deep Learning Methods for Proximal Inference via Maximum Moment Restriction Benjamin Kompa David R. Bellamy Thomas Kolokotrones J. M. Robins Andrew L. Beam 26 12 0 19 May 2022
Proximal Causal Inference for Marginal Counterfactual Survival Curves Andrew Ying Yifan Cui E. T. Tchetgen 21 10 0 27 Apr 2022
Partial Identification with Noisy Covariates: A Robust Optimization Approach Wenshuo Guo Mingzhang Yin Yixin Wang Michael I. Jordan 21 19 0 22 Feb 2022
Long-term Causal Inference Under Persistent Confounding via Data Combination Guido Imbens Nathan Kallus Xiaojie Mao Yuhao Wang CML 10 34 0 15 Feb 2022
Combining Experimental and Observational Data for Identification and Estimation of Long-Term Causal Effects AmirEmad Ghassami Alan Yang David Richardson I. Shpitser E. T. Tchetgen CML 8 8 0 26 Jan 2022
A Minimax Learning Approach to Off-Policy Evaluation in Confounded Partially Observable Markov Decision Processes C. Shi Masatoshi Uehara Jiawei Huang Nan Jiang OffRL 4 22 0 12 Nov 2021
Causal Inference with Hidden Mediators AmirEmad Ghassami Alan Yang I. Shpitser E. T. Tchetgen 11 5 0 04 Nov 2021
Proximal Reinforcement Learning: Efficient Off-Policy Evaluation in Partially Observed Markov Decision Processes Andrew Bennett Nathan Kallus OffRL 11 40 0 28 Oct 2021
Nonparametric inference about mean functionals of nonignorable nonresponse data without identifying the joint distribution Wei Li Wang Miao E. T. Tchetgen Tchetgen 10 13 0 12 Oct 2021
Many Proxy Controls Ben Deaner AI4CE 20 7 0 08 Oct 2021
Proximal Causal Inference for Complex Longitudinal Studies Andrew Ying Wang Miao Xu Shi E. T. Tchetgen 16 38 0 15 Sep 2021
The Proximal ID Algorithm I. Shpitser Zach Wood-Doughty E. T. Tchetgen CML 14 17 0 15 Aug 2021
Proximal Learning for Individualized Treatment Regimes Under Unmeasured Confounding Zhengling Qi Rui Miao Xiaoke Zhang CML 15 28 0 03 May 2021
Minimax Kernel Machine Learning for a Class of Doubly Robust Functionals with Application to Proximal Causal Inference AmirEmad Ghassami Andrew Ying I. Shpitser E. T. Tchetgen 14 43 0 07 Apr 2021
Causal Inference Under Unmeasured Confounding With Negative Controls: A Minimax Learning Approach Nathan Kallus Xiaojie Mao Masatoshi Uehara CML 14 65 0 25 Mar 2021
Valid Instrumental Variables Selection Methods using Negative Control Outcomes and Constructing Efficient Estimator Shunichiro Orihara 10 0 0 24 Feb 2021