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Selective machine learning of doubly robust functionals
v1v2v3v4v5v6 (latest)

Selective machine learning of doubly robust functionals

5 November 2019
Yifan Cui
E. T. Tchetgen
    OOD
ArXiv (abs)PDFHTML

Papers citing "Selective machine learning of doubly robust functionals"

12 / 12 papers shown
Forster-Warmuth Counterfactual Regression: A Unified Learning Approach
Forster-Warmuth Counterfactual Regression: A Unified Learning Approach
Yachong Yang
Arun K. Kuchibhotla
E. T. Tchetgen
339
8
0
31 Jul 2023
Adaptive debiased machine learning using data-driven model selection
  techniques
Adaptive debiased machine learning using data-driven model selection techniques
L. Laan
M. Carone
Alexander Luedtke
Mark van der Laan
243
12
0
24 Jul 2023
In Search of Insights, Not Magic Bullets: Towards Demystification of the
  Model Selection Dilemma in Heterogeneous Treatment Effect Estimation
In Search of Insights, Not Magic Bullets: Towards Demystification of the Model Selection Dilemma in Heterogeneous Treatment Effect EstimationInternational Conference on Machine Learning (ICML), 2023
Alicia Curth
M. Schaar
CML
270
34
0
06 Feb 2023
Optimal Treatment Regimes for Proximal Causal Learning
Optimal Treatment Regimes for Proximal Causal LearningNeural Information Processing Systems (NeurIPS), 2022
Tao Shen
Yifan Cui
CML
319
4
0
19 Dec 2022
DeepMed: Semiparametric Causal Mediation Analysis with Debiased Deep
  Learning
DeepMed: Semiparametric Causal Mediation Analysis with Debiased Deep LearningNeural Information Processing Systems (NeurIPS), 2022
Siqi Xu
Lin Liu
Zhong Liu
CMLMedIm
215
12
0
10 Oct 2022
Proximal Causal Inference for Marginal Counterfactual Survival Curves
Proximal Causal Inference for Marginal Counterfactual Survival Curves
Andrew Ying
Yifan Cui
E. T. Tchetgen
191
12
0
27 Apr 2022
Validating Causal Inference Methods
Validating Causal Inference MethodsInternational Conference on Machine Learning (ICML), 2022
Harsh Parikh
Carlos Varjao
Louise Xu
E. T. Tchetgen
CML
489
34
0
09 Feb 2022
The costs and benefits of uniformly valid causal inference with
  high-dimensional nuisance parameters
The costs and benefits of uniformly valid causal inference with high-dimensional nuisance parametersStatistical Science (Statist. Sci.), 2021
Niloofar Moosavi
J. Haggstrom
X. de Luna
231
16
0
05 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 InferenceInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2021
AmirEmad Ghassami
Andrew Ying
I. Shpitser
E. T. Tchetgen
271
48
0
07 Apr 2021
Regularizing Double Machine Learning in Partially Linear Endogenous
  Models
Regularizing Double Machine Learning in Partially Linear Endogenous ModelsElectronic Journal of Statistics (EJS), 2021
Corinne Emmenegger
Peter Buhlmann
226
11
0
29 Jan 2021
Semiparametric proximal causal inference
Semiparametric proximal causal inferenceJournal of the American Statistical Association (JASA), 2020
Yifan Cui
Hongming Pu
Xu Shi
Wang Miao
E. T. Tchetgen Tchetgen
431
128
0
17 Nov 2020
Assumption-lean inference for generalised linear model parameters
Assumption-lean inference for generalised linear model parameters
S. Vansteelandt
O. Dukes
CML
305
67
0
15 Jun 2020
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