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Quasi-Oracle Estimation of Heterogeneous Treatment Effects

13 December 2017

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

50 / 275 papers shown

Title
Causal Inference with Conditional Front-Door Adjustment and Identifiable Variational Autoencoder Ziqi Xu Debo Cheng Jiuyong Li Jixue Liu Lin Liu Kui Yu CML 74 9 0 03 Oct 2023
Towards Causal Foundation Model: on Duality between Causal Inference and Attention Jiaqi Zhang Joel Jennings Agrin Hilmkil Nick Pawlowski Cheng Zhang Chao Ma CML 112 14 0 01 Oct 2023
Fairness Implications of Heterogeneous Treatment Effect Estimation with Machine Learning Methods in Policy-making Patrick Rehill Nicholas Biddle SyDa CML 76 2 0 02 Sep 2023
Optimally weighted average derivative effects Oliver Hines Karla Diaz-Ordaz S. Vansteelandt CML 67 2 0 10 Aug 2023
Pareto Invariant Representation Learning for Multimedia Recommendation Shanshan Huang Haoxuan Li Qingsong Li Chunyuan Zheng Li Liu CML 94 12 0 09 Aug 2023
Variable importance for causal forests: breaking down the heterogeneity of treatment effects Clément Bénard Julie Josse CML 60 5 0 07 Aug 2023
Forster-Warmuth Counterfactual Regression: A Unified Learning Approach Yachong Yang Arun K. Kuchibhotla E. T. Tchetgen 54 3 0 31 Jul 2023
Adaptive debiased machine learning using data-driven model selection techniques L. Laan M. Carone Alexander Luedtke Mark van der Laan 74 9 0 24 Jul 2023
The Connection Between R-Learning and Inverse-Variance Weighting for Estimation of Heterogeneous Treatment Effects Aaron Fisher CML 53 1 0 19 Jul 2023
Efficient and Multiply Robust Risk Estimation under General Forms of Dataset Shift Hongxiang Qiu E. T. Tchetgen Yan Sun OOD 54 7 0 28 Jun 2023
A Meta-Learning Method for Estimation of Causal Excursion Effects to Assess Time-Varying Moderation Jieru Shi Walter Dempsey CML 49 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
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 47 3 0 20 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
Fair and Robust Estimation of Heterogeneous Treatment Effects for Policy Learning K. Kim J. Zubizarreta 89 7 0 06 Jun 2023
Multi-Study R-Learner for Estimating Heterogeneous Treatment Effects Across Studies Using Statistical Machine Learning Cathy Shyr Boyu Ren Prasad Patil Giovanni Parmigiani CML 74 1 0 01 Jun 2023
Learning Prescriptive ReLU Networks Wei-Ju Sun Asterios Tsiourvas 87 2 0 01 Jun 2023
Explicit Feature Interaction-aware Uplift Network for Online Marketing Dugang Liu Xing Tang Han Gao Fuyuan Lyu Xiuqiang He 80 16 0 01 Jun 2023
Reliable Off-Policy Learning for Dosage Combinations Jonas Schweisthal Dennis Frauen Valentyn Melnychuk Stefan Feuerriegel OffRL 57 12 0 31 May 2023
Dynamic Inter-treatment Information Sharing for Individualized Treatment Effects Estimation V. Chauhan Jiandong Zhou Ghadeer O. Ghosheh Soheila Molaei David Clifton 79 11 0 25 May 2023
Covariate balancing using the integral probability metric for causal inference Insung Kong Yuha Park Joonhyuk Jung Kwonsang Lee Yongdai Kim 99 8 0 23 May 2023
Causal Effect Estimation with Variational AutoEncoder and the Front Door Criterion Ziqi Xu Debo Cheng Jiuyong Li Jixue Liu Lin Liu Kui Yu CML 103 2 0 24 Apr 2023
B-Learner: Quasi-Oracle Bounds on Heterogeneous Causal Effects Under Hidden Confounding Miruna Oprescu Jacob Dorn Marah Ghoummaid Andrew Jesson Nathan Kallus Uri Shalit CML FedML 90 29 0 20 Apr 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
Practical Policy Optimization with Personalized Experimentation Mia Garrard Hanson Wang Benjamin Letham Shaun Singh Abbas Kazerouni ... Yin Huang Yichun Hu Chad Zhou Norm Zhou E. Bakshy 28 0 0 30 Mar 2023
Comparison of Methods that Combine Multiple Randomized Trials to Estimate Heterogeneous Treatment Effects Carly L Brantner Trang Quynh Nguyen Tengjie Tang Congwen Zhao H. Hong E. Stuart 62 4 0 28 Mar 2023
Counterfactually Fair Regression with Double Machine Learning Patrick Rehill FaML 56 1 0 21 Mar 2023
Spawrious: A Benchmark for Fine Control of Spurious Correlation Biases Aengus Lynch G. Dovonon Jean Kaddour Ricardo M. A. Silva 263 31 0 09 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
Semi-parametric inference based on adaptively collected data Licong Lin K. Khamaru Martin J. Wainwright OffRL 82 7 0 05 Mar 2023
Hyperparameter Tuning and Model Evaluation in Causal Effect Estimation Damian Machlanski Spyridon Samothrakis Paul Clarke ELM CML 80 9 0 02 Mar 2023
Causal isotonic calibration for heterogeneous treatment effects L. Laan Ernesto Ulloa-Pérez M. Carone Alexander Luedtke 92 12 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 60 4 0 23 Feb 2023
Quantifying Causes of Arctic Amplification via Deep Learning based Time-series Causal Inference Sahara Ali Omar Faruque Yiyi Huang Md. Osman Gani Aneesh Subramanian Nicole-Jienne Shchlegel Jianwu Wang CML 97 3 0 22 Feb 2023
A Survey on Causal Reinforcement Learning Yan Zeng Ruichu Cai Gang Hua Libo Huang Zijian Li CML 144 30 0 10 Feb 2023
An End-to-End Framework for Marketing Effectiveness Optimization under Budget Constraint Ziang Yan Shusen Wang Guorui Zhou Jingjian Lin Peng Jiang OffRL 39 8 0 09 Feb 2023
In Search of Insights, Not Magic Bullets: Towards Demystification of the Model Selection Dilemma in Heterogeneous Treatment Effect Estimation Alicia Curth M. Schaar CML 69 26 0 06 Feb 2023
Augmented Learning of Heterogeneous Treatment Effects via Gradient Boosting Trees Heng-Kai Chen M. LeBlanc James Y. Dai CML 70 0 0 02 Feb 2023
How to select predictive models for causal inference? M. Doutreligne Gaël Varoquaux ELM CML 70 2 0 01 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
On Heterogeneous Treatment Effects in Heterogeneous Causal Graphs R. Watson Hengrui Cai X. An S. Mclean Rui Song CML 52 2 0 29 Jan 2023
Zero-shot causal learning H. Nilforoshan Michael Moor Yusuf Roohani Yining Chen Anja vSurina Michihiro Yasunaga Sara Oblak J. Leskovec CML BDL OffRL 89 14 0 28 Jan 2023
Proximal Causal Learning of Conditional Average Treatment Effects Erik Sverdrup Yifan Cui CML 86 6 0 26 Jan 2023
Data-Driven Estimation of Heterogeneous Treatment Effects Christopher Tran Keith Burghardt Kristina Lerman Elena Zheleva CML 56 1 0 16 Jan 2023
Kernel-based off-policy estimation without overlap: Instance optimality beyond semiparametric efficiency Wenlong Mou Peng Ding Martin J. Wainwright Peter L. Bartlett OffRL 79 11 0 16 Jan 2023
Doubly Robust Counterfactual Classification K. Kim Edward H. Kennedy J. Zubizarreta OffRL 62 5 0 15 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
Continual Causal Effect Estimation: Challenges and Opportunities Zhixuan Chu Sheng Li CML 61 0 0 03 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