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
Stable Probability Weighting: Large-Sample and Finite-Sample Estimation and Inference Methods for Heterogeneous Causal Effects of Multivalued Treatments Under Limited Overlap Ganesh Karapakula 27 0 0 13 Jan 2023
Heterogeneous Synthetic Learner for Panel Data Ye Shen Runzhe Wan Hengrui Cai Rui Song 29 1 0 30 Dec 2022
Nonparametric Estimation of Conditional Incremental Effects Alec McClean Zach Branson Edward H. Kennedy CML 28 8 0 07 Dec 2022
Meta-analysis of individualized treatment rules via sign-coherency Jay Jojo Cheng J. Huling Guanhua Chen 38 0 0 28 Nov 2022
Flexible machine learning estimation of conditional average treatment effects: a blessing and a curse Richard Post Isabel L. van den Heuvel M. Petković Edwin R. van den Heuvel CML 30 1 0 29 Oct 2022
A Double Machine Learning Trend Model for Citizen Science Data Daniel Fink A. Johnston Matthew Strimas‐Mackey T. Auer W. Hochachka ... Lauren Oldham Jaromczyk O. Robinson Christopher Wood S. Kelling A. Rodewald 26 15 0 27 Oct 2022
Distributionally Robust Causal Inference with Observational Data Dimitris Bertsimas Kosuke Imai Michael Lingzhi Li OOD 65 9 0 15 Oct 2022
Transfer Learning on Heterogeneous Feature Spaces for Treatment Effects Estimation Ioana Bica M. Schaar OOD CML 38 20 0 08 Oct 2022
Semi-supervised Batch Learning From Logged Data Gholamali Aminian Armin Behnamnia R. Vega Laura Toni Chengchun Shi Hamid R. Rabiee Omar Rivasplata Miguel R. D. Rodrigues OffRL 28 0 0 15 Sep 2022
Normalizing Flows for Interventional Density Estimation Valentyn Melnychuk Dennis Frauen Stefan Feuerriegel 50 19 0 13 Sep 2022
Estimating individual treatment effects under unobserved confounding using binary instruments Dennis Frauen Stefan Feuerriegel CML 29 18 0 17 Aug 2022
Improving Data-driven Heterogeneous Treatment Effect Estimation Under Structure Uncertainty Christopher Tran Elena Zheleva CML 36 4 0 25 Jun 2022
Policy Learning with Asymmetric Counterfactual Utilities Eli Ben-Michael Kosuke Imai Zhichao Jiang OffRL 36 16 0 21 Jun 2022
Benchmarking Heterogeneous Treatment Effect Models through the Lens of Interpretability Jonathan Crabbé Alicia Curth Ioana Bica M. Schaar CML 24 16 0 16 Jun 2022
Efficient Heterogeneous Treatment Effect Estimation With Multiple Experiments and Multiple Outcomes Leon Yao Caroline Lo Israel Nir S. Tan Ariel Evnine Adam Lerer A. Peysakhovich CML 29 6 0 10 Jun 2022
Comparison of meta-learners for estimating multi-valued treatment heterogeneous effects Naoufal Acharki Ramiro Lugo A. Bertoncello Josselin Garnier CML 32 11 0 29 May 2022
Robust and Agnostic Learning of Conditional Distributional Treatment Effects Nathan Kallus M. Oprescu CML OOD 35 10 0 23 May 2022
What's the Harm? Sharp Bounds on the Fraction Negatively Affected by Treatment Nathan Kallus 38 22 0 20 May 2022
Flexible and Efficient Contextual Bandits with Heterogeneous Treatment Effect Oracles Aldo G. Carranza Sanath Kumar Krishnamurthy Susan Athey 21 1 0 30 Mar 2022
Calibration Error for Heterogeneous Treatment Effects Yizhe Xu Steve Yadlowsky 31 12 0 24 Mar 2022
GCF: Generalized Causal Forest for Heterogeneous Treatment Effect Estimation in Online Marketplace Shu Wan Chen Zheng Zhonggen Sun Mengfan Xu Xiaoqing Yang Hong-Tu Zhu Jiecheng Guo 31 7 0 21 Mar 2022
T-Cal: An optimal test for the calibration of predictive models Donghwan Lee Xinmeng Huang Hamed Hassani Yan Sun 22 20 0 03 Mar 2022
Minimax rates for heterogeneous causal effect estimation Edward H. Kennedy Sivaraman Balakrishnan James M. Robins Larry A. Wasserman CML 8 31 0 02 Mar 2022
Statistically Efficient Advantage Learning for Offline Reinforcement Learning in Infinite Horizons C. Shi Shuang Luo Yuan Le Hongtu Zhu R. Song OffRL OnRL 32 10 0 26 Feb 2022
Differentially Private Estimation of Heterogeneous Causal Effects Fengshi Niu Harsha Nori B. Quistorff R. Caruana Donald Ngwe A. Kannan CML 25 13 0 22 Feb 2022
Benign-Overfitting in Conditional Average Treatment Effect Prediction with Linear Regression Masahiro Kato Masaaki Imaizumi CML OOD 59 1 0 10 Feb 2022
A nonparametric doubly robust test for a continuous treatment effect Charles R. Doss Guangwei Weng Lan Wang I. Moscovice T. Chantarat 19 2 0 07 Feb 2022
Meta-Learners for Estimation of Causal Effects: Finite Sample Cross-Fit Performance Gabriel Okasa CML 19 6 0 30 Jan 2022
Treatment Effect Risk: Bounds and Inference Nathan Kallus CML 13 15 0 15 Jan 2022
A Large Scale Benchmark for Individual Treatment Effect Prediction and Uplift Modeling Eustache Diemert Artem Betlei Christophe Renaudin Massih-Reza Amini T. Gregoir Thibaud Rahier CML 33 10 0 19 Nov 2021
Evaluating Treatment Prioritization Rules via Rank-Weighted Average Treatment Effects Steve Yadlowsky S. Fleming N. Shah Emma Brunskill Stefan Wager 9 63 0 15 Nov 2021
Sequential Kernel Embedding for Mediated and Time-Varying Dose Response Curves Rahul Singh Liyuan Xu Arthur Gretton 37 3 0 06 Nov 2021
Improved inference for doubly robust estimators of heterogeneous treatment effects Hee-Choon Shin Joseph Antonelli 11 4 0 05 Nov 2021
Interpretable Personalized Experimentation Han Wu S. Tan Weiwei Li Mia Garrard Adam Obeng Drew Dimmery Shaun Singh Hanson Wang Daniel R. Jiang E. Bakshy 33 5 0 05 Nov 2021
SurvITE: Learning Heterogeneous Treatment Effects from Time-to-Event Data Alicia Curth Changhee Lee M. Schaar CML 30 30 0 26 Oct 2021
CAPITAL: Optimal Subgroup Identification via Constrained Policy Tree Search Hengrui Cai Wenbin Lu Rachel Marceau West D. Mehrotra Lingkang Huang 13 8 0 11 Oct 2021
Efficient Learning of Optimal Individualized Treatment Rules for Heteroscedastic or Misspecified Treatment-Free Effect Models Weibin Mo Yufeng Liu 30 9 0 06 Sep 2021
DoWhy: Addressing Challenges in Expressing and Validating Causal Assumptions Amit Sharma Vasilis Syrgkanis Cheng Zhang Emre Kıcıman 26 26 0 27 Aug 2021
On the Distinction Between "Conditional Average Treatment Effects" (CATE) and "Individual Treatment Effects" (ITE) Under Ignorability Assumptions Brian G. Vegetabile CML 14 19 0 10 Aug 2021
Identifiable Energy-based Representations: An Application to Estimating Heterogeneous Causal Effects Yao Zhang Jeroen Berrevoets M. Schaar CML 36 6 0 06 Aug 2021
Doing Great at Estimating CATE? On the Neglected Assumptions in Benchmark Comparisons of Treatment Effect Estimators Alicia Curth M. Schaar CML 22 7 0 28 Jul 2021
Demystifying statistical learning based on efficient influence functions Oliver Hines O. Dukes Karla Diaz-Ordaz S. Vansteelandt TDI 19 110 0 01 Jul 2021
On Inductive Biases for Heterogeneous Treatment Effect Estimation Alicia Curth M. Schaar CML 20 78 0 07 Jun 2021
Causal Effect Inference for Structured Treatments Jean Kaddour Yuchen Zhu Qi Liu Matt J. Kusner Ricardo M. A. Silva CML 185 50 0 03 Jun 2021
Risk Minimization from Adaptively Collected Data: Guarantees for Supervised and Policy Learning Aurélien F. Bibaut Antoine Chambaz Maria Dimakopoulou Nathan Kallus Mark van der Laan OffRL 11 13 0 03 Jun 2021
Median Optimal Treatment Regimes Liu Leqi Edward H. Kennedy 41 8 0 02 Mar 2021
Kernel Ridge Riesz Representers: Generalization, Mis-specification, and the Counterfactual Effective Dimension Rahul Singh CML 24 8 0 22 Feb 2021
Nonparametric Estimation of Heterogeneous Treatment Effects: From Theory to Learning Algorithms Alicia Curth M. Schaar CML 30 140 0 26 Jan 2021
Rejoinder: New Objectives for Policy Learning Nathan Kallus 52 1 0 05 Dec 2020
Deep Learning for Individual Heterogeneity M. Farrell Tengyuan Liang S. Misra BDL 29 17 0 28 Oct 2020