Towards optimal doubly robust estimation of heterogeneous causal effects

29 April 2020

Papers citing "Towards optimal doubly robust estimation of heterogeneous causal effects"

50 / 158 papers shown

Title
Conformal Counterfactual Inference under Hidden Confounding Zonghao Chen Ruocheng Guo Jean-François Ton Yang Liu CML OffRL 53 2 0 20 May 2024
Predictive Performance Comparison of Decision Policies Under Confounding Luke M. Guerdan Amanda Coston Kenneth Holstein Zhiwei Steven Wu OffRL 34 0 0 01 Apr 2024
Efficient and Sharp Off-Policy Evaluation in Robust Markov Decision Processes Andrew Bennett Nathan Kallus M. Oprescu Wen Sun Kaiwen Wang AAML OffRL 55 1 0 29 Mar 2024
Uplift Modeling Under Limited Supervision G. Panagopoulos Daniele Malitesta Fragkiskos D. Malliaros Jun Pang CML 46 0 0 28 Mar 2024
Limits of Approximating the Median Treatment Effect Raghavendra Addanki Siddharth Bhandari 30 0 0 15 Mar 2024
Unveiling the Potential of Robustness in Evaluating Causal Inference Models Yiyan Huang Cheuk Hang Leung Siyi Wang Yijun Li Qi Wu OOD CML 39 0 0 28 Feb 2024
Federated Learning for Estimating Heterogeneous Treatment Effects Disha Makhija Joydeep Ghosh Yejin Kim CML FedML 43 2 0 27 Feb 2024
Evaluating the Effectiveness of Index-Based Treatment Allocation Niclas Boehmer Yash Nair Sanket Shah Lucas Janson Aparna Taneja Milind Tambe 39 3 0 19 Feb 2024
Conformal Convolution and Monte Carlo Meta-learners for Predictive Inference of Individual Treatment Effects Jef Jonkers Jarne Verhaeghe Glenn Van Wallendael Luc Duchateau Sofie Van Hoecke 31 2 0 07 Feb 2024
Continuous Treatment Effects with Surrogate Outcomes Zhenghao Zeng David Arbour Avi Feller Raghavendra Addanki Ryan Rossi Ritwik Sinha Edward H. Kennedy CML 15 3 0 31 Jan 2024
Is Knowledge All Large Language Models Needed for Causal Reasoning? Hengrui Cai Shengjie Liu Rui Song LRM ELM 28 10 0 30 Dec 2023
RoME: A Robust Mixed-Effects Bandit Algorithm for Optimizing Mobile Health Interventions Easton K. Huch Jieru Shi Madeline R Abbott J. Golbus Alexander Moreno Walter Dempsey OffRL 24 0 0 11 Dec 2023
A Neural Framework for Generalized Causal Sensitivity Analysis Dennis Frauen F. Imrie Alicia Curth Valentyn Melnychuk Stefan Feuerriegel M. Schaar CML 36 10 0 27 Nov 2023
Bounds on Representation-Induced Confounding Bias for Treatment Effect Estimation Valentyn Melnychuk Dennis Frauen Stefan Feuerriegel CML 34 9 0 19 Nov 2023
Model Agnostic Explainable Selective Regression via Uncertainty Estimation Andrea Pugnana Carlos Mougan Dan Saattrup Nielsen 49 0 0 15 Nov 2023
CATE Lasso: Conditional Average Treatment Effect Estimation with High-Dimensional Linear Regression Masahiro Kato Masaaki Imaizumi CML 22 2 0 25 Oct 2023
Causal Q-Aggregation for CATE Model Selection Hui Lan Vasilis Syrgkanis CML 50 4 0 25 Oct 2023
Counterfactual Prediction Under Selective Confounding Sohaib Kiani Jared Barton Jon Sushinsky Lynda Heimbach Bo Luo CML 37 1 0 21 Oct 2023
Transparency challenges in policy evaluation with causal machine learning -- improving usability and accountability Patrick Rehill Nicholas Biddle CML ELM 42 3 0 20 Oct 2023
Causal Effect Estimation after Propensity Score Trimming with Continuous Treatments Zach Branson Edward H. Kennedy Sivaraman Balakrishnan Larry Wasserman CML 35 4 0 01 Sep 2023
Conformal Meta-learners for Predictive Inference of Individual Treatment Effects Ahmed Alaa Zaid Ahmad Mark van der Laan CML 35 16 0 28 Aug 2023
Optimally weighted average derivative effects Oliver Hines Karla Diaz-Ordaz S. Vansteelandt CML 34 2 0 10 Aug 2023
Pareto Invariant Representation Learning for Multimedia Recommendation Shanshan Huang Haoxuan Li Qingsong Li Chunyuan Zheng Li Liu CML 27 11 0 09 Aug 2023
Variable importance for causal forests: breaking down the heterogeneity of treatment effects Clément Bénard Julie Josse CML 39 5 0 07 Aug 2023
Forster-Warmuth Counterfactual Regression: A Unified Learning Approach Yachong Yang Arun K. Kuchibhotla E. T. Tchetgen 26 3 0 31 Jul 2023
The Connection Between R-Learning and Inverse-Variance Weighting for Estimation of Heterogeneous Treatment Effects Aaron Fisher CML 24 1 0 19 Jul 2023
Mitigating Adversarial Vulnerability through Causal Parameter Estimation by Adversarial Double Machine Learning Byung-Kwan Lee Junho Kim Yonghyun Ro AAML 33 9 0 14 Jul 2023
Efficient and Multiply Robust Risk Estimation under General Forms of Dataset Shift Hongxiang Qiu E. T. Tchetgen Yan Sun OOD 17 7 0 28 Jun 2023
A Meta-Learning Method for Estimation of Causal Excursion Effects to Assess Time-Varying Moderation Jieru Shi Walter Dempsey CML 23 4 0 28 Jun 2023
Incremental Profit per Conversion: a Response Transformation for Uplift Modeling in E-Commerce Promotions Hugo Manuel Proença Felipe Moraes 24 1 0 23 Jun 2023
Treatment Effects in Extreme Regimes Ahmed Aloui Ali Hasan Yuting Ng Miroslav Pajic Vahid Tarokh 11 0 0 20 Jun 2023
Assumption-lean falsification tests of rate double-robustness of double-machine-learning estimators Lin Liu Rajarshi Mukherjee J. M. Robins 26 1 0 18 Jun 2023
Three-way Cross-Fitting and Pseudo-Outcome Regression for Estimation of Conditional Effects and other Linear Functionals Aaron Fisher Virginia Fisher 24 3 0 12 Jun 2023
Fair and Robust Estimation of Heterogeneous Treatment Effects for Policy Learning K. Kim J. Zubizarreta 36 7 0 06 Jun 2023
Sharp Bounds for Generalized Causal Sensitivity Analysis Dennis Frauen Valentyn Melnychuk Stefan Feuerriegel CML 41 18 0 26 May 2023
Dynamic Inter-treatment Information Sharing for Individualized Treatment Effects Estimation V. Chauhan Jiandong Zhou Ghadeer O. Ghosheh Soheila Molaei David Clifton 30 8 0 25 May 2023
Meta-learning for heterogeneous treatment effect estimation with closed-form solvers Tomoharu Iwata Yoichi Chikahara CML FedML 36 0 0 19 May 2023
B-Learner: Quasi-Oracle Bounds on Heterogeneous Causal Effects Under Hidden Confounding M. Oprescu Jacob Dorn Marah Ghoummaid Andrew Jesson Nathan Kallus Uri Shalit CML FedML 32 25 0 20 Apr 2023
Comparison of Methods that Combine Multiple Randomized Trials to Estimate Heterogeneous Treatment Effects Carly L Brantner Trang Quynh Nguyen Tengjie Tang Congwen Zhao H. Hong E. Stuart 27 3 0 28 Mar 2023
Semi-parametric inference based on adaptively collected data Licong Lin K. Khamaru Martin J. Wainwright OffRL 39 6 0 05 Mar 2023
Causal isotonic calibration for heterogeneous treatment effects L. Laan Ernesto Ulloa-Pérez M. Carone Alexander Luedtke 31 11 0 27 Feb 2023
Understanding the Impact of Competing Events on Heterogeneous Treatment Effect Estimation from Time-to-Event Data Alicia Curth M. Schaar CML 34 3 0 23 Feb 2023
$New $\sqrt{n}$-consistent, numerically stable higher-order influence function estimators$ New $\sqrt{n}$ -consistent, numerically stable higher-order influence function estimators Lin Liu Chang Li 21 0 0 16 Feb 2023
In Search of Insights, Not Magic Bullets: Towards Demystification of the Model Selection Dilemma in Heterogeneous Treatment Effect Estimation Alicia Curth M. Schaar CML 15 25 0 06 Feb 2023
Robust Fitted-Q-Evaluation and Iteration under Sequentially Exogenous Unobserved Confounders David Bruns-Smith Angela Zhou OffRL 18 9 0 01 Feb 2023
How to select predictive models for causal inference? M. Doutreligne Gaël Varoquaux ELM CML 29 2 0 01 Feb 2023
Zero-shot causal learning H. Nilforoshan Michael Moor Yusuf Roohani Yining Chen Anja vSurina Michihiro Yasunaga Sara Oblak J. Leskovec CML BDL OffRL 24 11 0 28 Jan 2023
Proximal Causal Learning of Conditional Average Treatment Effects Erik Sverdrup Yifan Cui CML 30 4 0 26 Jan 2023
Data-Driven Estimation of Heterogeneous Treatment Effects Christopher Tran Keith Burghardt Kristina Lerman Elena Zheleva CML 32 1 0 16 Jan 2023
Doubly Robust Counterfactual Classification K. Kim Edward H. Kennedy J. Zubizarreta OffRL 33 5 0 15 Jan 2023