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Quasi-Oracle Estimation of Heterogeneous Treatment Effects

13 December 2017

Papers citing "Quasi-Oracle Estimation of Heterogeneous Treatment Effects"

25 / 275 papers shown

Title
Generalization Bounds and Representation Learning for Estimation of Potential Outcomes and Causal Effects Fredrik D. Johansson Uri Shalit Nathan Kallus David Sontag CML OOD 128 100 0 21 Jan 2020
A Loss-Function for Causal Machine-Learning I-Sheng Yang CML OOD 16 1 0 02 Jan 2020
Localized Debiased Machine Learning: Efficient Inference on Quantile Treatment Effects and Beyond Nathan Kallus Xiaojie Mao Masatoshi Uehara 64 27 0 30 Dec 2019
Estimation and Validation of Ratio-based Conditional Average Treatment Effects Using Observational Data Steve Yadlowsky Fabio Pellegrini F. Lionetto S. Braune L. Tian CML 16 16 0 15 Dec 2019
Group Average Treatment Effects for Observational Studies D. Jacob CML 82 20 0 07 Nov 2019
Targeted Estimation of Heterogeneous Treatment Effect in Observational Survival Analysis Jie Zhu B. Gallego CML 91 29 0 20 Oct 2019
Estimation of Bounds on Potential Outcomes For Decision Making Maggie Makar Fredrik D. Johansson John Guttag David Sontag 27 1 0 10 Oct 2019
Affordable Uplift: Supervised Randomization in Controlled Experiments Johannes Haupt D. Jacob R. M. Gubela Stefan Lessmann 92 5 0 01 Oct 2019
Uncovering Sociological Effect Heterogeneity using Machine Learning J. Brand Jiahui Xu Bernard Koch Pablo Geraldo CML 18 6 0 18 Sep 2019
Counterfactual Cross-Validation: Stable Model Selection Procedure for Causal Inference Models Yuta Saito Shota Yasui OOD CML 40 8 0 11 Sep 2019
Uplift Modeling for Multiple Treatments with Cost Optimization Zhenyu Zhao Totte Harinen 40 49 0 14 Aug 2019
Covariate-Powered Empirical Bayes Estimation Nikolaos Ignatiadis Stefan Wager 43 20 0 04 Jun 2019
Machine Learning Estimation of Heterogeneous Treatment Effects with Instruments Vasilis Syrgkanis Victor Lei Miruna Oprescu Maggie Hei Keith Battocchi Greg Lewis CML 50 73 0 24 May 2019
Learning When-to-Treat Policies Xinkun Nie Emma Brunskill Stefan Wager CML OffRL 82 92 0 23 May 2019
Experimental Evaluation of Individualized Treatment Rules Kosuke Imai Michael Lingzhi Li 65 39 0 14 May 2019
Inferring Heterogeneous Causal Effects in Presence of Spatial Confounding Muhammad Osama Dave Zachariah Thomas B. Schon 33 8 0 28 Jan 2019
Orthogonal Statistical Learning Dylan J. Foster Vasilis Syrgkanis 159 174 0 25 Jan 2019
Modified Causal Forests for Estimating Heterogeneous Causal Effects M. Lechner CML 40 49 0 22 Dec 2018
Local Linear Forests R. Friedberg J. Tibshirani Susan Athey Stefan Wager 157 92 0 30 Jul 2018
Regularized Orthogonal Machine Learning for Nonlinear Semiparametric Models Denis Nekipelov Vira Semenova Vasilis Syrgkanis 91 20 0 13 Jun 2018
Causal effects based on distributional distances Kwangho Kim Jisu Kim Edward H. Kennedy CML 44 19 0 08 Jun 2018
De-Biased Machine Learning of Global and Local Parameters Using Regularized Riesz Representers Victor Chernozhukov Whitney Newey Rahul Singh 105 93 0 23 Feb 2018
Estimation and Inference on Heterogeneous Treatment Effects in High-Dimensional Dynamic Panels under Weak Dependence Vira Semenova Matt Goldman Victor Chernozhukov Matt Taddy CML 66 13 0 28 Dec 2017
Automated versus do-it-yourself methods for causal inference: Lessons learned from a data analysis competition Vincent Dorie J. Hill Uri Shalit M. Scott D. Cervone CML 283 288 0 09 Jul 2017
Selective inference for effect modification via the lasso Qingyuan Zhao Dylan S. Small Ashkan Ertefaie CML 133 50 0 22 May 2017