Causal Inference Under Unmeasured Confounding With Negative Controls: A
Minimax Learning Approach

Causal Inference Under Unmeasured Confounding With Negative Controls: A Minimax Learning Approach

25 March 2021

Masatoshi Uehara

Papers citing "Causal Inference Under Unmeasured Confounding With Negative Controls: A Minimax Learning Approach"

11 / 11 papers shown

Title
Doubly Robust Proximal Causal Learning for Continuous Treatments Yong Wu Yanwei Fu Shouyan Wang Xinwei Sun 21 1 0 22 Sep 2023
Kernel Single Proxy Control for Deterministic Confounding Liyuan Xu A. Gretton CML 19 2 0 08 Aug 2023
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
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
Controlling for Latent Confounding with Triple Proxies Ben Deaner CML 14 0 0 28 Apr 2022
Off-Policy Confidence Interval Estimation with Confounded Markov Decision Process C. Shi Jin Zhu Ye Shen S. Luo Hong Zhu R. Song OffRL 13 30 0 22 Feb 2022
Causal Inference with Hidden Mediators AmirEmad Ghassami Alan Yang I. Shpitser E. T. Tchetgen 11 5 0 04 Nov 2021
Proximal Causal Inference for Complex Longitudinal Studies Andrew Ying Wang Miao Xu Shi E. T. Tchetgen 21 38 0 15 Sep 2021
Semiparametric proximal causal inference Yifan Cui Hongming Pu Xu Shi Wang Miao E. T. Tchetgen Tchetgen 16 100 0 17 Nov 2020