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Sharp Sensitivity Analysis for Inverse Propensity Weighting via Quantile Balancing

8 February 2021

Papers citing "Sharp Sensitivity Analysis for Inverse Propensity Weighting via Quantile Balancing"

23 / 23 papers shown

Title
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
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 183 119 0 11 Oct 2024
Meta-Learners for Partially-Identified Treatment Effects Across Multiple Environments Jonas Schweisthal Dennis Frauen M. Schaar Stefan Feuerriegel CML 100 7 0 04 Jun 2024
Efficient and Sharp Off-Policy Evaluation in Robust Markov Decision Processes Andrew Bennett Nathan Kallus Miruna Oprescu Wen Sun Kaiwen Wang AAML OffRL 87 1 0 29 Mar 2024
Defining Expertise: Applications to Treatment Effect Estimation Alihan Huyuk Qiyao Wei Alicia Curth M. Schaar CML 73 2 0 01 Mar 2024
Hidden yet quantifiable: A lower bound for confounding strength using randomized trials Piersilvio De Bartolomeis Javier Abad Konstantin Donhauser Fanny Yang CML 74 8 0 06 Dec 2023
Causal Fairness under Unobserved Confounding: A Neural Sensitivity Framework Maresa Schröder Dennis Frauen Stefan Feuerriegel CML 71 6 0 30 Nov 2023
A Neural Framework for Generalized Causal Sensitivity Analysis Dennis Frauen F. Imrie Alicia Curth Valentyn Melnychuk Stefan Feuerriegel M. Schaar CML 92 10 0 27 Nov 2023
Bounds on Representation-Induced Confounding Bias for Treatment Effect Estimation Valentyn Melnychuk Dennis Frauen Stefan Feuerriegel CML 83 10 0 19 Nov 2023
Confounding-Robust Policy Improvement with Human-AI Teams Ruijiang Gao Mingzhang Yin 444 4 0 13 Oct 2023
A Convex Framework for Confounding Robust Inference Kei Ishikawa Naio He Takafumi Kanamori OffRL 47 0 0 21 Sep 2023
Ensembled Prediction Intervals for Causal Outcomes Under Hidden Confounding Myrl G. Marmarelis Greg Ver Steeg Aram Galstyan Fred Morstatter CML OOD 97 5 0 15 Jun 2023
Partial Counterfactual Identification of Continuous Outcomes with a Curvature Sensitivity Model Valentyn Melnychuk Dennis Frauen Stefan Feuerriegel 120 11 0 02 Jun 2023
Sharp Bounds for Generalized Causal Sensitivity Analysis Dennis Frauen Valentyn Melnychuk Stefan Feuerriegel CML 120 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 90 29 0 20 Apr 2023
Kernel Conditional Moment Constraints for Confounding Robust Inference Kei Ishikawa Niao He OffRL 79 3 0 26 Feb 2023
Robust Fitted-Q-Evaluation and Iteration under Sequentially Exogenous Unobserved Confounders David Bruns-Smith Angela Zhou OffRL 54 10 0 01 Feb 2023
Robust Design and Evaluation of Predictive Algorithms under Unobserved Confounding Ashesh Rambachan Amanda Coston Edward H. Kennedy 96 4 0 19 Dec 2022
Sensitivity Analysis for Marginal Structural Models Matteo Bonvini Edward H. Kennedy V. Ventura Larry A. Wasserman CML 72 14 0 10 Oct 2022
Probabilistic Conformal Prediction Using Conditional Random Samples Zhendong Wang Ruijiang Gao Mingzhang Yin Mingyuan Zhou David M. Blei TPM 139 25 0 14 Jun 2022
Partial Identification of Dose Responses with Hidden Confounders Myrl G. Marmarelis E. Haddad Andrew Jesson N. Jahanshad Aram Galstyan Greg Ver Steeg CML 95 7 0 24 Apr 2022
Scalable Sensitivity and Uncertainty Analysis for Causal-Effect Estimates of Continuous-Valued Interventions Andrew Jesson A. Douglas P. Manshausen Maelys Solal N. Meinshausen P. Stier Y. Gal Uri Shalit CML 94 26 0 21 Apr 2022
Combining Observational and Experimental Datasets Using Shrinkage Estimators Evan T. R. Rosenman Guillaume W. Basse Art B. Owen Mike Baiocchi CML 66 63 0 16 Feb 2020