Approximate Residual Balancing: De-Biased Inference of Average Treatment Effects in High Dimensions

25 April 2016

Papers citing "Approximate Residual Balancing: De-Biased Inference of Average Treatment Effects in High Dimensions"

50 / 111 papers shown

Title
Inferring Outcome Means of Exponential Family Distributions Estimated by Deep Neural Networks Xuran Meng Yi Li BDL 25 0 0 12 Apr 2025
Program Evaluation with Remotely Sensed Outcomes Ashesh Rambachan Rahul Singh Davide Viviano 59 1 0 17 Nov 2024
Statistical Inference in High-dimensional Poisson Regression with Applications to Mediation Analysis Prabrisha Rakshit Zijian Guo 23 1 0 28 Oct 2024
Automatic debiasing of neural networks via moment-constrained learning Christian L. Hines Oliver J. Hines CML OOD 31 0 0 29 Sep 2024
U-learning for Prediction Inference via Combinatory Multi-Subsampling: With Applications to LASSO and Neural Networks Zhe Fei Yi Li AI4CE 23 1 0 22 Jul 2024
Causal Inference with Complex Treatments: A Survey Yingrong Wang Haoxuan Li Minqin Zhu Anpeng Wu Ruoxuan Xiong Fei Wu Kun Kuang CML 32 0 0 19 Jul 2024
Causal inference through multi-stage learning and doubly robust deep neural networks Yuqian Zhang Jelena Bradic OOD CML 27 0 0 11 Jul 2024
Stable Heterogeneous Treatment Effect Estimation across Out-of-Distribution Populations Yuling Zhang Anpeng Wu Kun Kuang Liang Du Zixun Sun Zhi Wang OODD 32 2 0 03 Jul 2024
C-Learner: Constrained Learning for Causal Inference and Semiparametric Statistics T. Cai Yuri Fonseca Kaiwen Hou Hongseok Namkoong CML 17 1 0 15 May 2024
Causal-StoNet: Causal Inference for High-Dimensional Complex Data Yaxin Fang Faming Liang CML 26 1 0 27 Mar 2024
Pareto-Optimal Estimation and Policy Learning on Short-term and Long-term Treatment Effects Yingrong Wang Anpeng Wu Haoxuan Li Weiming Liu Qiaowei Miao Ruoxuan Xiong Fei Wu Kun Kuang 42 0 0 05 Mar 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 13 1 0 08 Dec 2023
Uplift Modeling based on Graph Neural Network Combined with Causal Knowledge Haowen Wang Xinyan Ye Yangze Zhou Zhiyi Zhang L. Zhang Jing Jiang CML 19 0 0 14 Nov 2023
Estimating treatment effects from single-arm trials via latent-variable modeling Manuel Haussmann Tran Minh Son Le Viivi Halla-aho Samu Kurki Jussi Leinonen Miika Koskinen Samuel Kaski Harri Lähdesmäki CML 21 0 0 06 Nov 2023
High Precision Causal Model Evaluation with Conditional Randomization Chao Ma Cheng Zhang CML 22 1 0 03 Nov 2023
Addressing Dynamic and Sparse Qualitative Data: A Hilbert Space Embedding of Categorical Variables Anirban Mukherjee Hannah H. Chang CML 16 0 0 22 Aug 2023
RCT Rejection Sampling for Causal Estimation Evaluation Katherine A. Keith Sergey Feldman David Jurgens Jonathan Bragg Rohit Bhattacharya CML 22 7 0 27 Jul 2023
A Meta-Learning Method for Estimation of Causal Excursion Effects to Assess Time-Varying Moderation Jieru Shi Walter Dempsey CML 15 4 0 28 Jun 2023
Root-n consistent semiparametric learning with high-dimensional nuisance functions under minimal sparsity Lin Liu Yuhao Wang 30 0 0 07 May 2023
Augmented balancing weights as linear regression David Bruns-Smith O. Dukes Avi Feller Elizabeth L. Ogburn 27 10 0 27 Apr 2023
Inference on Optimal Dynamic Policies via Softmax Approximation Qizhao Chen Morgane Austern Vasilis Syrgkanis OffRL 25 1 0 08 Mar 2023
Statistical Inference and Large-scale Multiple Testing for High-dimensional Regression Models T. Tony Cai Zijian Guo Yin Xia 55 6 0 25 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 19 0 0 13 Jan 2023
Instrumental Variables in Causal Inference and Machine Learning: A Survey Anpeng Wu Kun Kuang Ruoxuan Xiong Fei Wu SyDa CML 20 6 0 12 Dec 2022
Confounder Balancing for Instrumental Variable Regression with Latent Variable Anpeng Wu Kun Kuang Ruoxuan Xiong Bo Li Fei Wu CML 33 0 0 18 Nov 2022
Prediction Sets for High-Dimensional Mixture of Experts Models Adel Javanmard S. Shao Jacob Bien 31 5 0 30 Oct 2022
Causal Effect of Functional Treatment Ruoxu Tan Wei Huang Zheng-Wei Zhang G. Yin CML 23 5 0 01 Oct 2022
Falsification before Extrapolation in Causal Effect Estimation Zeshan Hussain Michael Oberst M. Shih David Sontag CML 37 8 0 27 Sep 2022
Finite- and Large- Sample Inference for Model and Coefficients in High-dimensional Linear Regression with Repro Samples P. Wang Min-ge Xie Linjun Zhang 27 5 0 19 Sep 2022
Data-Driven Causal Effect Estimation Based on Graphical Causal Modelling: A Survey Debo Cheng Jiuyong Li Lin Liu Jixue Liu T. Le CML 27 26 0 20 Aug 2022
Outcome Assumptions and Duality Theory for Balancing Weights David Bruns-Smith Avi Feller 14 5 0 17 Mar 2022
Estimating causal effects with optimization-based methods: A review and empirical comparison Martin Cousineau V. Verter S. Murphy J. Pineau CML 8 9 0 28 Feb 2022
Debiased Graph Neural Networks with Agnostic Label Selection Bias Shaohua Fan Xiao Wang Chuan Shi Kun Kuang Nian Liu Bai Wang AI4CE 29 38 0 19 Jan 2022
Generalizing Graph Neural Networks on Out-Of-Distribution Graphs Shaohua Fan Xiao Wang Chuan Shi Peng Cui Bai Wang CML OOD OODD AI4CE 37 81 0 20 Nov 2021
Projected State-action Balancing Weights for Offline Reinforcement Learning Jiayi Wang Zhengling Qi Raymond K. W. Wong OffRL 17 15 0 10 Sep 2021
Towards Out-Of-Distribution Generalization: A Survey Jiashuo Liu Zheyan Shen Yue He Xingxuan Zhang Renzhe Xu Han Yu Peng Cui CML OOD 29 513 0 31 Aug 2021
Semiparametric Estimation of Long-Term Treatment Effects Jiafeng Chen David M. Ritzwoller 20 19 0 30 Jul 2021
Causal Inference with Panel Data under Temporal and Spatial Interference Ye Wang 16 4 0 29 Jun 2021
An Interpretable Neural Network for Parameter Inference Johann Pfitzinger 13 0 0 10 Jun 2021
The costs and benefits of uniformly valid causal inference with high-dimensional nuisance parameters Niloofar Moosavi J. Haggstrom X. de Luna 19 14 0 05 May 2021
Proximal Learning for Individualized Treatment Regimes Under Unmeasured Confounding Zhengling Qi Rui Miao Xiaoke Zhang CML 26 28 0 03 May 2021
Automatic Double Machine Learning for Continuous Treatment Effects Sylvia Klosin 31 8 0 21 Apr 2021
Deconfounding Scores: Feature Representations for Causal Effect Estimation with Weak Overlap Alexander DÁmour Alexander M. Franks CML 11 10 0 12 Apr 2021
Minimax Kernel Machine Learning for a Class of Doubly Robust Functionals with Application to Proximal Causal Inference AmirEmad Ghassami Andrew Ying I. Shpitser E. T. Tchetgen 19 43 0 07 Apr 2021
Dynamic covariate balancing: estimating treatment effects over time with potential local projections Davide Viviano Jelena Bradic 21 0 0 01 Mar 2021
Covariate balancing for causal inference on categorical and continuous treatments Seong-ho Lee Yanyuan Ma X. de Luna CML 9 4 0 28 Feb 2021
Estimating Average Treatment Effects with Support Vector Machines Alexander Tarr Kosuke Imai 18 8 0 23 Feb 2021
Estimating Average Treatment Effects via Orthogonal Regularization Tobias Hatt Stefan Feuerriegel CML 148 35 0 21 Jan 2021
Kernel Methods for Unobserved Confounding: Negative Controls, Proxies, and Instruments Rahul Singh CML 23 39 0 18 Dec 2020
Debiased Inverse Propensity Score Weighting for Estimation of Average Treatment Effects with High-Dimensional Confounders Yuhao Wang Rajen Dinesh Shah 92 15 0 17 Nov 2020