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Bounds on Representation-Induced Confounding Bias for Treatment Effect Estimation

19 November 2023

Papers citing "Bounds on Representation-Induced Confounding Bias for Treatment Effect Estimation"

41 / 41 papers shown

Title
Quantifying Aleatoric Uncertainty of the Treatment Effect: A Novel Orthogonal Learner Valentyn Melnychuk Stefan Feuerriegel Mihaela van der Schaar CML 237 5 0 05 Nov 2024
Causal machine learning for predicting treatment outcomes Stefan Feuerriegel Dennis Frauen Valentyn Melnychuk Jonas Schweisthal Konstantin Hess Alicia Curth Stefan Bauer Niki Kilbertus Isaac S. Kohane Mihaela van der Schaar CML 171 109 0 11 Oct 2024
Optimal Transport for Treatment Effect Estimation Hao Wang Zhichao Chen Jiajun Fan Haoxuan Li Tianqiao Liu Weiming Liu Quanyu Dai Yichao Wang Zhenhua Dong Ruiming Tang OT CML 65 36 0 27 Oct 2023
Bayesian Neural Controlled Differential Equations for Treatment Effect Estimation Konstantin Hess Valentyn Melnychuk Dennis Frauen Stefan Feuerriegel 49 15 0 26 Oct 2023
Data-Driven Allocation of Preventive Care With Application to Diabetes Mellitus Type II Mathias Kraus Stefan Feuerriegel M. Saar-Tsechansky 55 12 0 14 Aug 2023
Sharp Bounds for Generalized Causal Sensitivity Analysis Dennis Frauen Valentyn Melnychuk Stefan Feuerriegel CML 104 19 0 26 May 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 68 29 0 20 Apr 2023
Sensitivity Analysis for Marginal Structural Models Matteo Bonvini Edward H. Kennedy V. Ventura Larry A. Wasserman CML 64 14 0 10 Oct 2022
Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations Nabeel Seedat F. Imrie Alexis Bellot Zhaozhi Qian M. Schaar OOD CML 52 52 0 16 Jun 2022
Causal Transformer for Estimating Counterfactual Outcomes Valentyn Melnychuk Dennis Frauen Stefan Feuerriegel CML 86 98 0 14 Apr 2022
Minimax rates for heterogeneous causal effect estimation Edward H. Kennedy Sivaraman Balakrishnan James M. Robins Larry A. Wasserman CML 77 31 0 02 Mar 2022
Causal Effect Identification in Cluster DAGs Tarandeep Anand A. Ribeiro Jin Tian Elias Bareinboim CML 51 17 0 22 Feb 2022
Treatment Effect Risk: Bounds and Inference Nathan Kallus CML 124 17 0 15 Jan 2022
On Inductive Biases for Heterogeneous Treatment Effect Estimation Alicia Curth M. Schaar CML 183 84 0 07 Jun 2021
Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding Andrew Jesson Sören Mindermann Y. Gal Uri Shalit CML 59 55 0 08 Mar 2021
Sharp Sensitivity Analysis for Inverse Propensity Weighting via Quantile Balancing Jacob Dorn Kevin Guo 160 58 0 08 Feb 2021
Nonparametric Estimation of Heterogeneous Treatment Effects: From Theory to Learning Algorithms Alicia Curth M. Schaar CML 163 149 0 26 Jan 2021
Counterfactual Representation Learning with Balancing Weights Serge Assaad Shuxi Zeng Chenyang Tao Shounak Datta Nikhil Mehta Ricardo Henao Fan Li Lawrence Carin CML OOD 131 64 0 23 Oct 2020
Identifying Causal-Effect Inference Failure with Uncertainty-Aware Models Andrew Jesson Sören Mindermann Uri Shalit Y. Gal CML 50 74 0 01 Jul 2020
Counterfactual Predictions under Runtime Confounding Amanda Coston Edward H. Kennedy Alexandra Chouldechova OOD OffRL 49 28 0 30 Jun 2020
Towards optimal doubly robust estimation of heterogeneous causal effects Edward H. Kennedy CML 165 326 0 29 Apr 2020
Estimating Counterfactual Treatment Outcomes over Time Through Adversarially Balanced Representations Ioana Bica Ahmed Alaa James Jordon M. Schaar BDL CML 63 186 0 10 Feb 2020
Generalization Bounds and Representation Learning for Estimation of Potential Outcomes and Causal Effects Fredrik D. Johansson Uri Shalit Nathan Kallus David Sontag CML OOD 78 100 0 21 Jan 2020
Noise Regularization for Conditional Density Estimation Jonas Rothfuss Fabio Ferreira S. Boehm Simon Walther Maxim Ulrich Tamim Asfour Andreas Krause 37 32 0 21 Jul 2019
Neural Spline Flows Conor Durkan Artur Bekasov Iain Murray George Papamakarios DRL 183 777 0 10 Jun 2019
Adversarial Balancing-based Representation Learning for Causal Effect Inference with Observational Data Xin Du Lei Sun W. Duivesteijn Alexander G. Nikolaev Mykola Pechenizkiy OOD CML 46 43 0 30 Apr 2019
Interval Estimation of Individual-Level Causal Effects Under Unobserved Confounding Nathan Kallus Xiaojie Mao Angela Zhou CML 59 94 0 05 Oct 2018
Perfect Match: A Simple Method for Learning Representations For Counterfactual Inference With Neural Networks Patrick Schwab Lorenz Linhardt W. Karlen CML BDL 54 111 0 01 Oct 2018
Learning Weighted Representations for Generalization Across Designs Fredrik D. Johansson Nathan Kallus Uri Shalit David Sontag OOD 68 87 0 23 Feb 2018
Conditional Density Estimation with Bayesian Normalising Flows Brian L. Trippe Richard Turner BDL 78 84 0 14 Feb 2018
Bayesian Nonparametric Causal Inference: Information Rates and Learning Algorithms Ahmed Alaa Mihaela van der Schaar CML 53 43 0 24 Dec 2017
Quasi-Oracle Estimation of Heterogeneous Treatment Effects Xinkun Nie Stefan Wager CML 156 653 0 13 Dec 2017
Causal Consistency of Structural Equation Models Paul Kishan Rubenstein S. Weichwald Stephan Bongers Joris M. Mooij Dominik Janzing Moritz Grosse-Wentrup Bernhard Schölkopf CML 83 129 0 04 Jul 2017
Meta-learners for Estimating Heterogeneous Treatment Effects using Machine Learning Sören R. Künzel Jasjeet Sekhon Peter J. Bickel Bin Yu CML 164 928 0 12 Jun 2017
Bayesian Inference of Individualized Treatment Effects using Multi-task Gaussian Processes Ahmed Alaa M. Schaar CML 173 304 0 10 Apr 2017
Double/Debiased/Neyman Machine Learning of Treatment Effects Victor Chernozhukov Denis Chetverikov Mert Demirer E. Duflo Christian B. Hansen Whitney Newey CML FedML 149 351 0 30 Jan 2017
Instrumental variables as bias amplifiers with general outcome and confounding Peng Ding T. VanderWeele Jamie Robins CML 58 67 0 16 Jan 2017
Learning Representations for Counterfactual Inference Fredrik D. Johansson Uri Shalit David Sontag CML OOD BDL 282 729 0 12 May 2016
Estimation and Inference of Heterogeneous Treatment Effects using Random Forests Stefan Wager Susan Athey SyDa CML 352 2,490 0 14 Oct 2015
To Adjust or Not to Adjust? Sensitivity Analysis of M-Bias and Butterfly-Bias Peng Ding Luke W. Miratrix CML 58 124 0 02 Aug 2014
BART: Bayesian additive regression trees H. Chipman E. George R. McCulloch 156 1,794 0 19 Jun 2008