Estimation and Inference of Heterogeneous Treatment Effects using Random Forests

14 October 2015

Papers citing "Estimation and Inference of Heterogeneous Treatment Effects using Random Forests"

50 / 285 papers shown

Title
VLUCI: Variational Learning of Unobserved Confounders for Counterfactual Inference Yonghe Zhao Q. Huang Siwei Wu Yun Peng Huashan Sun BDL CML 26 0 0 02 Aug 2023
A Look into Causal Effects under Entangled Treatment in Graphs: Investigating the Impact of Contact on MRSA Infection Jing Ma Chen Chen A. Vullikanti Ritwick Mishra Gregory R. Madden Daniel Borrajo Jundong Li CML 38 4 0 17 Jul 2023
Medoid splits for efficient random forests in metric spaces Matthieu Bulté Helle Sorensen 26 4 0 29 Jun 2023
Should I Stop or Should I Go: Early Stopping with Heterogeneous Populations Hammaad Adam Fan Yin Huibin Mary Hu Neil A. Tenenholtz Lorin Crawford Lester W. Mackey Allison Koenecke 35 1 0 20 Jun 2023
Fair and Robust Estimation of Heterogeneous Treatment Effects for Policy Learning K. Kim J. Zubizarreta 47 7 0 06 Jun 2023
Learning Prescriptive ReLU Networks Wei-Ju Sun Asterios Tsiourvas 47 2 0 01 Jun 2023
Dynamic Inter-treatment Information Sharing for Individualized Treatment Effects Estimation V. Chauhan Jiandong Zhou Ghadeer O. Ghosheh Soheila Molaei David Clifton 35 9 0 25 May 2023
An Efficient Doubly-Robust Test for the Kernel Treatment Effect Diego Martinez-Taboada Aaditya Ramdas Edward H. Kennedy OOD 38 5 0 26 Apr 2023
Linking a predictive model to causal effect estimation Jiuyong Li Lin Liu Ziqi Xu Ha Xuan Tran T. Le Jixue Liu CML 48 0 0 10 Apr 2023
Matched Machine Learning: A Generalized Framework for Treatment Effect Inference With Learned Metrics Marco Morucci Cynthia Rudin A. Volfovsky CML FedML 29 1 0 03 Apr 2023
Semi-parametric inference based on adaptively collected data Licong Lin K. Khamaru Martin J. Wainwright OffRL 54 6 0 05 Mar 2023
Causal isotonic calibration for heterogeneous treatment effects L. Laan Ernesto Ulloa-Pérez M. Carone Alexander Luedtke 45 11 0 27 Feb 2023
Extrapolated cross-validation for randomized ensembles Jin-Hong Du Pratik V. Patil Kathryn Roeder Arun K. Kuchibhotla 33 5 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 39 3 0 23 Feb 2023
Confidence and Uncertainty Assessment for Distributional Random Forests Jeffrey Näf Corinne Emmenegger Peter Buhlmann N. Meinshausen 43 3 0 11 Feb 2023
Causal Inference Based Single-branch Ensemble Trees For Uplift Modeling Fanglan Zheng Menghan Wang Kun Li Jiang Tian Xiaojia Xiang CML 29 0 0 03 Feb 2023
Augmented Learning of Heterogeneous Treatment Effects via Gradient Boosting Trees Heng-Kai Chen M. LeBlanc James Y. Dai CML 43 0 0 02 Feb 2023
How to select predictive models for causal inference? M. Doutreligne Gaël Varoquaux ELM CML 34 2 0 01 Feb 2023
Falsification of Internal and External Validity in Observational Studies via Conditional Moment Restrictions Zeshan Hussain M. Shih Michael Oberst Ilker Demirel D. Sontag 39 8 0 30 Jan 2023
Integrating Earth Observation Data into Causal Inference: Challenges and Opportunities Connor Jerzak Fredrik D. Johansson Adel Daoud CML 48 11 0 30 Jan 2023
Proximal Causal Learning of Conditional Average Treatment Effects Erik Sverdrup Yifan Cui CML 44 4 0 26 Jan 2023
Data-Driven Estimation of Heterogeneous Treatment Effects Christopher Tran Keith Burghardt Kristina Lerman Elena Zheleva CML 37 1 0 16 Jan 2023
Doubly Robust Counterfactual Classification K. Kim Edward H. Kennedy J. Zubizarreta OffRL 41 5 0 15 Jan 2023
Deep Causal Learning for Robotic Intelligence Yongqian Li CML 50 5 0 23 Dec 2022
Policy learning for many outcomes of interest: Combining optimal policy trees with multi-objective Bayesian optimisation Patrick Rehill Nicholas Biddle 20 0 0 13 Dec 2022
On regression-adjusted imputation estimators of the average treatment effect Zhexiao Lin Fang Han 15 6 0 11 Dec 2022
Doubly Robust Kernel Statistics for Testing Distributional Treatment Effects Jake Fawkes Robert Hu R. Evans Dino Sejdinovic OOD 44 3 0 09 Dec 2022
Criteria for Classifying Forecasting Methods Tim Januschowski Jan Gasthaus Bernie Wang David Salinas Valentin Flunkert Michael Bohlke-Schneider Laurent Callot AI4TS 38 173 0 07 Dec 2022
Counterfactual Learning with General Data-generating Policies Yusuke Narita Kyohei Okumura Akihiro Shimizu Kohei Yata CML OffRL 50 0 0 04 Dec 2022
Direct Heterogeneous Causal Learning for Resource Allocation Problems in Marketing Hao Zhou Shaoming Li Guibin Jiang Jiaqi Zheng Dong Wang 40 17 0 28 Nov 2022
Meta-analysis of individualized treatment rules via sign-coherency Jay Jojo Cheng J. Huling Guanhua Chen 55 0 0 28 Nov 2022
Counterfactual Learning with Multioutput Deep Kernels A. Caron G. Baio I. Manolopoulou BDL CML OffRL 49 1 0 20 Nov 2022
On the Pointwise Behavior of Recursive Partitioning and Its Implications for Heterogeneous Causal Effect Estimation M. D. Cattaneo Jason M. Klusowski Peter M. Tian 38 4 0 19 Nov 2022
RISE: Robust Individualized Decision Learning with Sensitive Variables Xiaoqing Ellen Tan Zhengling Qi C. Seymour Lu Tang OffRL 31 8 0 12 Nov 2022
$Individualized and Global Feature Attributions for Gradient Boosted Trees in the Presence of $\ell_2$ Regularization$ Individualized and Global Feature Attributions for Gradient Boosted Trees in the Presence of $\ell_2$ Regularization Qingyao Sun 39 2 0 08 Nov 2022
Deep Causal Learning: Representation, Discovery and Inference Zizhen Deng Xiaolong Zheng Hu Tian D. Zeng CML BDL 55 11 0 07 Nov 2022
Personalizing Sustainable Agriculture with Causal Machine Learning Georgios Giannarakis Vasileios Sitokonstantinou R. Lorilla C. Kontoes 28 9 0 06 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 28 16 0 27 Oct 2022
Learning Individual Treatment Effects under Heterogeneous Interference in Networks Ziyu Zhao Yuqi Bai Kun Kuang Ruoxuan Xiong Fei Wu CML 31 7 0 25 Oct 2022
Causal Inference for De-biasing Motion Estimation from Robotic Observational Data Junhong Xu Kai-Li Yin Jason M. Gregory Lantao Liu CML 30 3 0 17 Oct 2022
Distributionally Robust Causal Inference with Observational Data Dimitris Bertsimas Kosuke Imai Michael Lingzhi Li OOD 79 9 0 15 Oct 2022
Transfer Learning on Heterogeneous Feature Spaces for Treatment Effects Estimation Ioana Bica M. Schaar OOD CML 43 20 0 08 Oct 2022
Improving uplift model evaluation on RCT data B. Bokelmann Stefan Lessmann 34 0 0 05 Oct 2022
Local and Regional Counterfactual Rules: Summarized and Robust Recourses Salim I. Amoukou Nicolas Brunel 35 0 0 29 Sep 2022
Falsification before Extrapolation in Causal Effect Estimation Zeshan Hussain Michael Oberst M. Shih David Sontag CML 54 8 0 27 Sep 2022
Covariance regression with random forests Cansu Alakus Denis Larocque A. Labbe 44 7 0 16 Sep 2022
Stochastic Tree Ensembles for Estimating Heterogeneous Effects Nikolay M. Krantsevich Jingyu He P. R. Hahn CML 37 13 0 15 Sep 2022
Moderately-Balanced Representation Learning for Treatment Effects with Orthogonality Information Yiyan Huang Cheuk Hang Leung Shumin Ma Qi Wu DongDong Wang Zhixiang Huang OOD CML 47 3 0 05 Sep 2022
The Infinitesimal Jackknife and Combinations of Models Indrayudh Ghosal Yunzhe Zhou Giles Hooker 54 4 0 31 Aug 2022