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Semiparametric proximal causal inference

Semiparametric proximal causal inference

17 November 2020
Yifan Cui
Hongming Pu
Xu Shi
Wang Miao
E. T. Tchetgen Tchetgen
ArXivPDFHTML

Papers citing "Semiparametric proximal causal inference"

15 / 15 papers shown
Title
Detecting clinician implicit biases in diagnoses using proximal causal inference
Detecting clinician implicit biases in diagnoses using proximal causal inference
Kara Liu
Russ Altman
Vasilis Syrgkanis
CML
70
0
0
27 Jan 2025
Deep Learning Methods for Proximal Inference via Maximum Moment
  Restriction
Deep Learning Methods for Proximal Inference via Maximum Moment Restriction
Benjamin Kompa
David R. Bellamy
Thomas Kolokotrones
J. M. Robins
Andrew L. Beam
55
14
0
19 May 2022
Long-term Causal Inference Under Persistent Confounding via Data
  Combination
Long-term Causal Inference Under Persistent Confounding via Data Combination
Guido Imbens
Nathan Kallus
Xiaojie Mao
Yuhao Wang
CML
67
47
0
15 Feb 2022
Proximal Causal Learning with Kernels: Two-Stage Estimation and Moment
  Restriction
Proximal Causal Learning with Kernels: Two-Stage Estimation and Moment Restriction
Afsaneh Mastouri
Yuchen Zhu
Limor Gultchin
Anna Korba
Ricardo M. A. Silva
Matt J. Kusner
Arthur Gretton
Krikamol Muandet
CML
37
61
0
10 May 2021
Minimax Kernel Machine Learning for a Class of Doubly Robust Functionals
  with Application to Proximal Causal Inference
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
47
43
0
07 Apr 2021
Causal Inference Under Unmeasured Confounding With Negative Controls: A
  Minimax Learning Approach
Causal Inference Under Unmeasured Confounding With Negative Controls: A Minimax Learning Approach
Nathan Kallus
Xiaojie Mao
Masatoshi Uehara
CML
57
67
0
25 Mar 2021
Kernel Methods for Unobserved Confounding: Negative Controls, Proxies,
  and Instruments
Kernel Methods for Unobserved Confounding: Negative Controls, Proxies, and Instruments
Rahul Singh
CML
54
40
0
18 Dec 2020
On Deep Instrumental Variables Estimate
On Deep Instrumental Variables Estimate
Ruiqi Liu
Zuofeng Shang
Guang Cheng
38
27
0
30 Apr 2020
Selective machine learning of doubly robust functionals
Selective machine learning of doubly robust functionals
Yifan Cui
E. T. Tchetgen
OOD
61
23
0
05 Nov 2019
Deep Generalized Method of Moments for Instrumental Variable Analysis
Deep Generalized Method of Moments for Instrumental Variable Analysis
Andrew Bennett
Nathan Kallus
Tobias Schnabel
57
125
0
29 May 2019
Model-assisted inference for treatment effects using regularized
  calibrated estimation with high-dimensional data
Model-assisted inference for treatment effects using regularized calibrated estimation with high-dimensional data
Z. Tan
43
88
0
30 Jan 2018
Double/Debiased/Neyman Machine Learning of Treatment Effects
Double/Debiased/Neyman Machine Learning of Treatment Effects
Victor Chernozhukov
Denis Chetverikov
Mert Demirer
E. Duflo
Christian B. Hansen
Whitney Newey
CML
FedML
110
348
0
30 Jan 2017
Locally Robust Semiparametric Estimation
Locally Robust Semiparametric Estimation
Victor Chernozhukov
J. Escanciano
Hidehiko Ichimura
Whitney Newey
J. M. Robins
74
206
0
29 Jul 2016
Confounder Adjustment in Multiple Hypothesis Testing
Confounder Adjustment in Multiple Hypothesis Testing
Jingshu Wang
Qingyuan Zhao
Trevor Hastie
Art B. Owen
CML
32
105
0
17 Aug 2015
Higher order influence functions and minimax estimation of nonlinear
  functionals
Higher order influence functions and minimax estimation of nonlinear functionals
J. M. Robins
Lingling Li
E. T. Tchetgen
A. van der Vaart
162
241
0
20 May 2008
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