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Meta-learners for Estimating Heterogeneous Treatment Effects using Machine Learning

12 June 2017

Papers citing "Meta-learners for Estimating Heterogeneous Treatment Effects using Machine Learning"

50 / 191 papers shown

Title
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 77 4 0 17 Jul 2023
A Meta-Learning Method for Estimation of Causal Excursion Effects to Assess Time-Varying Moderation Jieru Shi Walter Dempsey CML 46 4 0 28 Jun 2023
Incremental Profit per Conversion: a Response Transformation for Uplift Modeling in E-Commerce Promotions Hugo Manuel Proença Felipe Moraes 56 1 0 23 Jun 2023
Three-way Cross-Fitting and Pseudo-Outcome Regression for Estimation of Conditional Effects and other Linear Functionals Aaron Fisher Virginia Fisher 48 3 0 12 Jun 2023
Task-specific experimental design for treatment effect estimation Beth D. Connolly Kim Moore Tobias Schwedes Alexander Adam Gary Willis Ilya Feige Christopher Frye CML 61 3 0 08 Jun 2023
Fair and Robust Estimation of Heterogeneous Treatment Effects for Policy Learning K. Kim J. Zubizarreta 89 7 0 06 Jun 2023
Sharp Bounds for Generalized Causal Sensitivity Analysis Dennis Frauen Valentyn Melnychuk Stefan Feuerriegel CML 120 19 0 26 May 2023
Integrating Nearest Neighbors with Neural Network Models for Treatment Effect Estimation Niki Kiriakidou Christos Diou CML 45 4 0 11 May 2023
Linking a predictive model to causal effect estimation Jiuyong Li Lin Liu Ziqi Xu Ha Xuan Tran T. Le Jixue Liu CML 73 0 0 10 Apr 2023
Approaching an unknown communication system by latent space exploration and causal inference Gašper Beguš Andrej Leban Shane Gero 45 4 0 20 Mar 2023
KDSM: An uplift modeling framework based on knowledge distillation and sample matching Chang Sun Qianying Li Guanxiang Wang S. Xu Yitong Liu 45 0 0 06 Mar 2023
Scalable End-to-End ML Platforms: from AutoML to Self-serve I. Markov P. Apostolopoulos Mia Garrard Tianyu Qie Yin Huang ... Anika Li Cesar Cardoso George Han Ryan Maghsoudian Norm Zhou LRM 75 2 0 27 Feb 2023
Causal isotonic calibration for heterogeneous treatment effects L. Laan Ernesto Ulloa-Pérez M. Carone Alexander Luedtke 92 12 0 27 Feb 2023
Counterfactual Prediction Under Outcome Measurement Error Luke M. Guerdan Amanda Coston Kenneth Holstein Zhiwei Steven Wu 81 15 0 22 Feb 2023
Confidence and Uncertainty Assessment for Distributional Random Forests Jeffrey Näf Corinne Emmenegger Peter Buhlmann N. Meinshausen 61 4 0 11 Feb 2023
Selective Uncertainty Propagation in Offline RL Sanath Kumar Krishnamurthy Shrey Modi Tanmay Gangwani S. Katariya Branislav Kveton A. Rangi OffRL 216 0 0 01 Feb 2023
Data-Driven Estimation of Heterogeneous Treatment Effects Christopher Tran Keith Burghardt Kristina Lerman Elena Zheleva CML 56 1 0 16 Jan 2023
Stable Probability Weighting: Large-Sample and Finite-Sample Estimation and Inference Methods for Heterogeneous Causal Effects of Multivalued Treatments Under Limited Overlap Ganesh Karapakula 61 0 0 13 Jan 2023
Efficient and robust transfer learning of optimal individualized treatment regimes with right-censored survival data Pan Zhao Julie Josse Shu Yang OffRL 77 3 0 13 Jan 2023
An Adaptive Kernel Approach to Federated Learning of Heterogeneous Causal Effects Thanh Vinh Vo Arnab Bhattacharyya Young Lee Tze-Yun Leong FedML 59 22 0 01 Jan 2023
Heterogeneous Synthetic Learner for Panel Data Ye Shen Runzhe Wan Hengrui Cai Rui Song 96 1 0 30 Dec 2022
Policy learning for many outcomes of interest: Combining optimal policy trees with multi-objective Bayesian optimisation Patrick Rehill Nicholas Biddle 50 0 0 13 Dec 2022
Nonparametric Estimation of Conditional Incremental Effects Alec McClean Zach Branson Edward H. Kennedy CML 60 8 0 07 Dec 2022
Evaluating Digital Agriculture Recommendations with Causal Inference Ilias Tsoumas Georgios Giannarakis Vasileios Sitokonstantinou Alkiviadis Koukos D. Loka Nikolaos S. Bartsotas C. Kontoes Ioannis Athanasiadis 47 12 0 30 Nov 2022
Applications of statistical causal inference in software engineering Julien Siebert CML 111 35 0 21 Nov 2022
BENK: The Beran Estimator with Neural Kernels for Estimating the Heterogeneous Treatment Effect Stanislav R. Kirpichenko Lev V. Utkin A. Konstantinov CML 98 0 0 19 Nov 2022
RISE: Robust Individualized Decision Learning with Sensitive Variables Xiaoqing Ellen Tan Zhengling Qi C. Seymour Lu Tang OffRL 65 8 0 12 Nov 2022
NESTER: An Adaptive Neurosymbolic Method for Causal Effect Estimation Abbavaram Gowtham Reddy V. Balasubramanian CML 55 0 0 08 Nov 2022
Robust Direct Learning for Causal Data Fusion Xinyu Li Yilin Li Daixin Wang Longfei Li Jun Zhou CML 55 1 0 01 Nov 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 58 16 0 27 Oct 2022
Adversarial De-confounding in Individualised Treatment Effects Estimation Vinod Kumar Chauhan Soheila Molaei Marzia Hoque Tania Anshul Thakur T. Zhu David Clifton CML 46 14 0 19 Oct 2022
Transfer Learning on Heterogeneous Feature Spaces for Treatment Effects Estimation Ioana Bica M. Schaar OOD CML 72 22 0 08 Oct 2022
Generalized Kernel Regularized Least Squares Qing Chang Max Goplerud 51 5 0 28 Sep 2022
Causal Proxy Models for Concept-Based Model Explanations Zhengxuan Wu Karel DÓosterlinck Atticus Geiger Amir Zur Christopher Potts MILM 132 37 0 28 Sep 2022
Estimating individual treatment effects under unobserved confounding using binary instruments Dennis Frauen Stefan Feuerriegel CML 91 20 0 17 Aug 2022
Constrained Prescriptive Trees via Column Generation Shivaram Subramanian Wei-Ju Sun Youssef Drissi M. Ettl 79 9 0 20 Jul 2022
Heterogeneous Treatment Effect with Trained Kernels of the Nadaraya-Watson Regression A. Konstantinov Stanislav R. Kirpichenko Lev V. Utkin CML 54 4 0 19 Jul 2022
Device-Cloud Collaborative Recommendation via Meta Controller Jiangchao Yao Feng Wang Xichen Ding Shaohu Chen Bo Han Jingren Zhou Hongxia Yang 104 18 0 07 Jul 2022
What Makes Forest-Based Heterogeneous Treatment Effect Estimators Work? Susanne Dandl Torsten Hothorn H. Seibold Erik Sverdrup Stefan Wager A. Zeileis CML 71 11 0 21 Jun 2022
Benchmarking Heterogeneous Treatment Effect Models through the Lens of Interpretability Jonathan Crabbé Alicia Curth Ioana Bica M. Schaar CML 110 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 57 7 0 10 Jun 2022
Estimating and Mitigating the Congestion Effect of Curbside Pick-ups and Drop-offs: A Causal Inference Approach Xiaohui Liu Sean Qian Hock-Hai Teo Weichao Ma 95 13 0 05 Jun 2022
Feature Selection for Discovering Distributional Treatment Effect Modifiers Yoichi Chikahara M. Yamada H. Kashima CML 51 5 0 01 Jun 2022
CEBaB: Estimating the Causal Effects of Real-World Concepts on NLP Model Behavior Eldar David Abraham Karel DÓosterlinck Amir Feder Y. Gat Atticus Geiger Christopher Potts Roi Reichart Zhengxuan Wu CML 122 47 0 27 May 2022
Causal Machine Learning for Healthcare and Precision Medicine Pedro Sanchez J. Voisey Tian Xia Hannah I. Watson Alison Q. OÑeil Sotirios A. Tsaftaris OOD CML 98 125 0 23 May 2022
Robust and Agnostic Learning of Conditional Distributional Treatment Effects Nathan Kallus Miruna Oprescu OOD CML 122 12 0 23 May 2022
What's the Harm? Sharp Bounds on the Fraction Negatively Affected by Treatment Nathan Kallus 76 23 0 20 May 2022
Searching for subgroup-specific associations while controlling the false discovery rate M. Sesia Tianshu Sun 85 0 0 17 May 2022
Multiple Domain Causal Networks Tianhui Zhou IV WilliamE.Carson M. H. Klein David Carlson CML 37 0 0 13 May 2022
Flexible and Efficient Contextual Bandits with Heterogeneous Treatment Effect Oracles Aldo G. Carranza Sanath Kumar Krishnamurthy Susan Athey 48 1 0 30 Mar 2022