v1v2v3v4v5v6 (latest)

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
Learning Causally Predictable Outcomes from Psychiatric Longitudinal Data Eric V. Strobl CML 5 0 0 01 Jul 2025
Hybrid Meta-learners for Estimating Heterogeneous Treatment Effects Zhongyuan Liang L. Laan Ahmed Alaa 16 0 0 16 Jun 2025
CausalPFN: Amortized Causal Effect Estimation via In-Context Learning Vahid Balazadeh Hamidreza Kamkari Valentin Thomas Benson Li Junwei Ma Jesse C. Cresswell Rahul G. Krishnan CML 15 0 0 09 Jun 2025
Do-PFN: In-Context Learning for Causal Effect Estimation Jake Robertson Arik Reuter Siyuan Guo Noah Hollmann Frank Hutter Bernhard Schölkopf CML 53 0 0 06 Jun 2025
A Diffusion-Based Method for Learning the Multi-Outcome Distribution of Medical Treatments Yuchen Ma Jonas Schweisthal Hengrui Zhang Stefan Feuerriegel OOD CML 50 0 0 02 Jun 2025
Doubly Robust Alignment for Large Language Models Erhan Xu Kai Ye Hongyi Zhou Luhan Zhu Francesco Quinzan Chengchun Shi 29 0 0 01 Jun 2025
Estimating Misreporting in the Presence of Genuine Modification: A Causal Perspective Dylan Zapzalka Trenton Chang Lindsay Warrenburg Sae-Hwan Park Daniel K. Shenfeld Ravi B. Parikh Jenna Wiens Maggie Makar 22 0 0 29 May 2025
M-learner:A Flexible And Powerful Framework To Study Heterogeneous Treatment Effect In Mediation Model Xingyu Li Qing Liu Tony Jiang Hong Amy Xia Brian P. Hobbs Peng Wei 45 0 0 23 May 2025
Deconfounded Warm-Start Thompson Sampling with Applications to Precision Medicine Prateek Jaiswal Esmaeil Keyvanshokooh Junyu Cao 47 0 0 22 May 2025
Treatment Effect Estimation for Optimal Decision-Making Dennis Frauen Valentyn Melnychuk Jonas Schweisthal Mihaela van der Schaar Stefan Feuerriegel CML 63 0 0 19 May 2025
Forests for Differences: Robust Causal Inference Beyond Parametric DiD Hugo Gobato Souto Francisco Louzada Neto 61 0 0 14 May 2025
Causal Predictive Optimization and Generation for Business AI Liyang Zhao Olurotimi Seton Himadeep Reddy Reddivari Suvendu Jena Shadow Zhao Rachit Kumar Changshuai Wei CML 121 0 0 14 May 2025
Reinforcement Learning for Individual Optimal Policy from Heterogeneous Data Rui Miao Babak Shahbaba Annie Qu OffRL 110 0 0 14 May 2025
Conditional Front-door Adjustment for Heterogeneous Treatment Assignment Effect Estimation Under Non-adherence Winston Chen Trenton Chang Jenna Wiens CML 68 0 0 08 May 2025
Extended Fiducial Inference for Individual Treatment Effects via Deep Neural Networks Sehwan Kim F. Liang FedML 93 0 0 04 May 2025
Statistical Learning for Heterogeneous Treatment Effects: Pretraining, Prognosis, and Prediction Maximilian Schuessler Erik Sverdrup Robert Tibshirani CML 88 0 0 01 May 2025
Long-term Causal Inference via Modeling Sequential Latent Confounding Weilin Chen Ruichu Cai Yuguang Yan Zijian Li José Miguel Hernández-Lobato CML 163 1 0 26 Feb 2025
Leveraging a Simulator for Learning Causal Representations from Post-Treatment Covariates for CATE Lokesh Nagalapatti Pranava Singhal Avishek Ghosh Sunita Sarawagi CML 131 0 0 07 Feb 2025
Conformal Inference of Individual Treatment Effects Using Conditional Density Estimates Baozhen Wang Xingye Qiao 201 2 0 28 Jan 2025
A New Transformation Approach for Uplift Modeling with Binary Outcome Kun Li Jiang Tian 113 0 0 10 Jan 2025
Session-Level Dynamic Ad Load Optimization using Offline Robust Reinforcement Learning Tao Liu Qi Xu Wei Shi Zhigang Hua Shuang Yang OffRL 87 0 0 09 Jan 2025
Double Machine Learning for Static Panel Models with Fixed Effects Paul Clarke Annalivia Polselli 171 3 0 03 Jan 2025
A Deep Subgrouping Framework for Precision Drug Repurposing via Emulating Clinical Trials on Real-world Patient Data Seungyeon Lee Ruoqi Liu Feixiong Cheng Ping Zhang 58 0 0 31 Dec 2024
Practical Performative Policy Learning with Strategic Agents Qianyi Chen Ying Chen Bo Li 218 0 0 02 Dec 2024
Comparing Targeting Strategies for Maximizing Social Welfare with Limited Resources Vibhhu Sharma Bryan Wilder 111 1 0 11 Nov 2024
Quantifying Aleatoric Uncertainty of the Treatment Effect: A Novel Orthogonal Learner Valentyn Melnychuk Stefan Feuerriegel Mihaela van der Schaar CML 272 5 0 05 Nov 2024
Testing Generalizability in Causal Inference Daniel de Vassimon Manela Linying Yang Robin J. Evans 78 0 0 05 Nov 2024
DiffPO: A causal diffusion model for learning distributions of potential outcomes Yuchen Ma Valentyn Melnychuk Jonas Schweisthal Stefan Feuerriegel DiffM 188 7 0 11 Oct 2024
Conformal Prediction: A Data Perspective Xiaofan Zhou Baiting Chen Yu Gui Lu Cheng 1.0K 5 0 09 Oct 2024
Model-agnostic meta-learners for estimating heterogeneous treatment effects over time Dennis Frauen Konstantin Hess Stefan Feuerriegel 156 7 0 07 Jul 2024
CURLS: Causal Rule Learning for Subgroups with Significant Treatment Effect Jiehui Zhou Linxiao Yang Xingyu Liu Xinyue Gu Lin Sun Wei Chen CML 75 0 0 01 Jul 2024
Causal Responder Detection Tzviel Frostig Oshri Machluf Amitay Kamber Elad Berkman Raviv Pryluk CML 43 1 0 25 Jun 2024
Compositional Models for Estimating Causal Effects Purva Pruthi David D. Jensen CML 225 0 0 25 Jun 2024
Iterative Causal Segmentation: Filling the Gap between Market Segmentation and Marketing Strategy Kaihua Ding Jingsong Cui Mohammad Soltani Jing Jin CML OOD 52 0 0 23 May 2024
Conformal Counterfactual Inference under Hidden Confounding Zonghao Chen Ruocheng Guo Jean-François Ton Yang Liu CML OffRL 214 3 0 20 May 2024
Bounding Causal Effects with Leaky Instruments David S. Watson Jordan Penn L. Gunderson Gecia Bravo Hermsdorff Afsaneh Mastouri Ricardo M. A. Silva CML 56 1 0 05 Apr 2024
Triple/Debiased Lasso for Statistical Inference of Conditional Average Treatment Effects Masahiro Kato CML 70 1 0 05 Mar 2024
Defining Expertise: Applications to Treatment Effect Estimation Alihan Huyuk Qiyao Wei Alicia Curth M. Schaar CML 78 2 0 01 Mar 2024
Conformal Convolution and Monte Carlo Meta-learners for Predictive Inference of Individual Treatment Effects Jef Jonkers Jarne Verhaeghe Glenn Van Wallendael Luc Duchateau Sofie Van Hoecke 458 2 0 07 Feb 2024
Disentangled Latent Representation Learning for Tackling the Confounding M-Bias Problem in Causal Inference Debo Cheng Yang Xie Ziqi Xu Jiuyong Li Lin Liu Jixue Liu Yinghao Zhang Zaiwen Feng CML BDL 60 1 0 08 Dec 2023
Bounds on Representation-Induced Confounding Bias for Treatment Effect Estimation Valentyn Melnychuk Dennis Frauen Stefan Feuerriegel CML 87 10 0 19 Nov 2023
CATE Estimation With Potential Outcome Imputation From Local Regression Ahmed Aloui Juncheng Dong Cat P. Le Vahid Tarokh CML 45 2 0 07 Nov 2023
Causal Q-Aggregation for CATE Model Selection Hui Lan Vasilis Syrgkanis CML 107 4 0 25 Oct 2023
Faithful Explanations of Black-box NLP Models Using LLM-generated Counterfactuals Y. Gat Nitay Calderon Amir Feder Alexander Chapanin Amit Sharma Roi Reichart 133 36 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
Conformal Meta-learners for Predictive Inference of Individual Treatment Effects Ahmed Alaa Zaid Ahmad Mark van der Laan CML 197 16 0 28 Aug 2023
A Two-Part Machine Learning Approach to Characterizing Network Interference in A/B Testing Yuan. Yuan Kristen M. Altenburger 74 5 0 18 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
Forster-Warmuth Counterfactual Regression: A Unified Learning Approach Yachong Yang Arun K. Kuchibhotla E. T. Tchetgen 54 3 0 31 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