Removing Hidden Confounding by Experimental Grounding

27 October 2018

Papers citing "Removing Hidden Confounding by Experimental Grounding"

20 / 20 papers shown

Title
A Cautionary Tale on Integrating Studies with Disparate Outcome Measures for Causal Inference Harsh Parikh Trang Quynh Nguyen Elizabeth A. Stuart Kara E. Rudolph Caleb H. Miles CML 17 0 0 16 May 2025
Nonparametric Heterogeneous Long-term Causal Effect Estimation via Data Combination Weilin Chen Ruichu Cai Junjie Wan Zeqin Yang José Miguel Hernández-Lobato 55 1 0 26 Feb 2025
Long-term Causal Inference via Modeling Sequential Latent Confounding Weilin Chen Ruichu Cai Yuguang Yan Zhifeng Hao José Miguel Hernández-Lobato CML 84 1 0 26 Feb 2025
Automatic Double Reinforcement Learning in Semiparametric Markov Decision Processes with Applications to Long-Term Causal Inference Lars van der Laan David Hubbard Allen Tran Nathan Kallus Aurélien F. Bibaut OffRL 39 0 0 12 Jan 2025
Benchmarks for Reinforcement Learning with Biased Offline Data and Imperfect Simulators Ori Linial Guy Tennenholtz Uri Shalit OffRL 46 1 0 30 Jun 2024
Adaptive-TMLE for the Average Treatment Effect based on Randomized Controlled Trial Augmented with Real-World Data Mark van der Laan Sky Qiu L. Laan Lars van der Laan 41 8 0 12 May 2024
Strategy to select most efficient RCT samples based on observational data Wenqi Shi Xi Lin 19 0 0 09 Nov 2022
Transfer Learning on Heterogeneous Feature Spaces for Treatment Effects Estimation Ioana Bica M. Schaar OOD CML 25 20 0 08 Oct 2022
Falsification before Extrapolation in Causal Effect Estimation Zeshan Hussain Michael Oberst M. Shih David Sontag CML 45 8 0 27 Sep 2022
Detecting hidden confounding in observational data using multiple environments R. Karlsson Jesse H. Krijthe CML OOD 42 12 0 27 May 2022
Combining Observational and Randomized Data for Estimating Heterogeneous Treatment Effects Tobias Hatt Jeroen Berrevoets Alicia Curth Stefan Feuerriegel M. Schaar CML 52 29 0 25 Feb 2022
ADCB: An Alzheimer's disease benchmark for evaluating observational estimators of causal effects N. M. Kinyanjui Fredrik D. Johansson CML 27 0 0 12 Nov 2021
Conditional Cross-Design Synthesis Estimators for Generalizability in Medicaid Irina Degtiar T. Layton Jacob Wallace Sherri Rose CML 46 5 0 27 Sep 2021
Obtaining Causal Information by Merging Datasets with MAXENT Sergio Hernan Garrido Mejia Elke Kirschbaum Dominik Janzing CML 18 9 0 15 Jul 2021
Quantum causal inference in the presence of hidden common causes: An entropic approach Mohammad Ali Javidian Vaneet Aggarwal Z. Jacob CML 13 2 0 24 Apr 2021
Causal Decision Making and Causal Effect Estimation Are Not the Same... and Why It Matters Carlos Fernández-Loría F. Provost CML 11 42 0 08 Apr 2021
Multi-Source Causal Inference Using Control Variates Wenshuo Guo S. Wang Peng Ding Yixin Wang Michael I. Jordan CML 55 18 0 30 Mar 2021
A Review of Generalizability and Transportability Irina Degtiar Sherri Rose CML 34 210 0 23 Feb 2021
Combining Observational and Experimental Datasets Using Shrinkage Estimators Evan T. R. Rosenman Guillaume W. Basse Art B. Owen Mike Baiocchi CML 21 61 0 16 Feb 2020
A Survey of Learning Causality with Data: Problems and Methods Ruocheng Guo Lu Cheng Jundong Li P. R. Hahn Huan Liu CML 32 168 0 25 Sep 2018