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Recursive Partitioning for Heterogeneous Causal Effects

5 April 2015

Papers citing "Recursive Partitioning for Heterogeneous Causal Effects"

38 / 188 papers shown

Title
Counterfactual Mean Embeddings Krikamol Muandet Motonobu Kanagawa Sorawit Saengkyongam S. Marukatat CML OffRL 101 40 0 22 May 2018
Causal Queries from Observational Data in Biological Systems via Bayesian Networks: An Empirical Study in Small Networks Alex E. White Matthieu Vignes CML 63 5 0 04 May 2018
A comparison of methods for model selection when estimating individual treatment effects Alejandro Schuler M. Baiocchi Robert Tibshirani N. Shah CML 87 59 0 14 Apr 2018
Deep Learning for Causal Inference V. Ramachandra CML BDL 62 19 0 01 Mar 2018
Active Learning with Logged Data Songbai Yan Kamalika Chaudhuri T. Javidi 159 27 0 25 Feb 2018
Learning Optimal Policies from Observational Data Onur Atan W. Zame M. Schaar CML OOD OffRL 68 18 0 23 Feb 2018
Learning Weighted Representations for Generalization Across Designs Fredrik D. Johansson Nathan Kallus Uri Shalit David Sontag OOD 83 87 0 23 Feb 2018
DeepMatch: Balancing Deep Covariate Representations for Causal Inference Using Adversarial Training Nathan Kallus CML OOD 81 77 0 15 Feb 2018
Global Model Interpretation via Recursive Partitioning Chengliang Yang Anand Rangarajan Sanjay Ranka FAtt 65 80 0 11 Feb 2018
How to Make Causal Inferences Using Texts Naoki Egami Christian Fong Justin Grimmer Margaret E. Roberts Brandon M Stewart CML 90 143 0 06 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
Bayesian Nonparametric Causal Inference: Information Rates and Learning Algorithms Ahmed Alaa Mihaela van der Schaar CML 73 43 0 24 Dec 2017
Quasi-Oracle Estimation of Heterogeneous Treatment Effects Xinkun Nie Stefan Wager CML 202 658 0 13 Dec 2017
Causal nearest neighbor rules for optimal treatment regimes Xin Zhou Michael R. Kosorok CML 45 16 0 22 Nov 2017
A Practically Competitive and Provably Consistent Algorithm for Uplift Modeling Yan Zhao X. Fang D. Simchi-Levi OffRL 42 20 0 12 Sep 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
Machine-Learning Tests for Effects on Multiple Outcomes J. Ludwig S. Mullainathan Jann Spiess 28 17 0 05 Jul 2017
Some methods for heterogeneous treatment effect estimation in high-dimensions Scott Powers Junyang Qian Kenneth Jung Alejandro Schuler N. Shah Trevor Hastie Robert Tibshirani CML 87 219 0 01 Jul 2017
A Comparison of Resampling and Recursive Partitioning Methods in Random Forest for Estimating the Asymptotic Variance Using the Infinitesimal Jackknife C. Brokamp M. Rao P. Ryan R. Jandarov 30 3 0 19 Jun 2017
Deep Counterfactual Networks with Propensity-Dropout Ahmed Alaa M. Weisz M. Schaar CML OOD BDL 68 86 0 19 Jun 2017
Meta-learners for Estimating Heterogeneous Treatment Effects using Machine Learning Sören R. Künzel Jasjeet Sekhon Peter J. Bickel Bin Yu CML 225 934 0 12 Jun 2017
Selective inference for effect modification via the lasso Qingyuan Zhao Dylan S. Small Ashkan Ertefaie CML 133 50 0 22 May 2017
Bayesian Inference of Individualized Treatment Effects using Multi-task Gaussian Processes Ahmed Alaa M. Schaar CML 193 304 0 10 Apr 2017
Estimation and Inference on Nonlinear and Heterogeneous Effects Marc Ratkovic D. Tingley 46 11 0 16 Mar 2017
Policy Learning with Observational Data Susan Athey Stefan Wager CML OffRL 459 183 0 09 Feb 2017
Learning causal effects from many randomized experiments using regularized instrumental variables A. Peysakhovich Dean Eckles CML 112 23 0 04 Jan 2017
Counterfactual Prediction with Deep Instrumental Variables Networks Jason S. Hartford Greg Lewis Kevin Leyton-Brown Matt Taddy CML OOD 190 49 0 30 Dec 2016
Constructing Effective Personalized Policies Using Counterfactual Inference from Biased Data Sets with Many Features Onur Atan W. Zame Qiaojun Feng M. Schaar OffRL CML 69 13 0 23 Dec 2016
Combining observational and experimental data to find heterogeneous treatment effects A. Peysakhovich Akos Lada CML 55 36 0 08 Nov 2016
Generalized Random Forests Susan Athey J. Tibshirani Stefan Wager 359 1,374 0 05 Oct 2016
On the Safety of Machine Learning: Cyber-Physical Systems, Decision Sciences, and Data Products Kush R. Varshney H. Alemzadeh 158 225 0 05 Oct 2016
Model Selection for Treatment Choice: Penalized Welfare Maximization Eric Mbakop Max Tabord-Meehan 272 67 0 11 Sep 2016
Recursive Partitioning for Personalization using Observational Data Nathan Kallus CML 284 100 0 31 Aug 2016
High-dimensional regression adjustments in randomized experiments Stefan Wager Wenfei Du Jonathan E. Taylor Robert Tibshirani 299 117 0 22 Jul 2016
Decomposing Treatment Effect Variation Peng Ding Avi Feller Luke W. Miratrix CML 112 82 0 21 May 2016
Causal Falling Rule Lists Fulton Wang Cynthia Rudin CML 73 21 0 18 Oct 2015
Estimation and Inference of Heterogeneous Treatment Effects using Random Forests Stefan Wager Susan Athey SyDa CML 407 2,506 0 14 Oct 2015
Causal Decision Trees Jiuyong Li Saisai Ma T. Le Lin Liu Jixue Liu CML 117 59 0 16 Aug 2015