Removing Hidden Confounding by Experimental Grounding

27 October 2018

Papers citing "Removing Hidden Confounding by Experimental Grounding"

33 / 33 papers shown

Title
Semiparametric Double Reinforcement Learning with Applications to Long-Term Causal Inference Lars van der Laan David Hubbard Allen Tran Nathan Kallus Aurélien F. Bibaut OffRL 79 0 0 01 Jul 2025
Deconfounded Warm-Start Thompson Sampling with Applications to Precision Medicine Prateek Jaiswal Esmaeil Keyvanshokooh Junyu Cao 57 0 0 22 May 2025
Long-term Causal Inference via Modeling Sequential Latent Confounding Weilin Chen Ruichu Cai Yuguang Yan Zijian Li José Miguel Hernández-Lobato CML 165 1 0 26 Feb 2025
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 92 9 0 12 May 2024
A Double Machine Learning Approach to Combining Experimental and Observational Data Harsh Parikh Marco Morucci Vittorio Orlandi Sudeepa Roy Cynthia Rudin A. Volfovsky 49 8 0 04 Jul 2023
Causal Effect Estimation from Observational and Interventional Data Through Matrix Weighted Linear Estimators Klaus-Rudolf Kladny Julius von Kügelgen Bernhard Schölkopf Michael Muehlebach CML 33 0 0 09 Jun 2023
Transfer Learning on Heterogeneous Feature Spaces for Treatment Effects Estimation Ioana Bica M. Schaar OOD CML 72 22 0 08 Oct 2022
Falsification before Extrapolation in Causal Effect Estimation Zeshan Hussain Michael Oberst M. Shih David Sontag CML 95 9 0 27 Sep 2022
Heterogeneous Treatment Effect with Trained Kernels of the Nadaraya-Watson Regression A. Konstantinov Stanislav R. Kirpichenko Lev V. Utkin CML 54 4 0 19 Jul 2022
Detecting hidden confounding in observational data using multiple environments R. Karlsson Jesse H. Krijthe CML OOD 94 13 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 90 32 0 25 Feb 2022
Long-term Causal Inference Under Persistent Confounding via Data Combination Guido Imbens Nathan Kallus Xiaojie Mao Yuhao Wang CML 115 49 0 15 Feb 2022
Generalizing Clinical Trials with Convex Hulls Eric V. Strobl Thomas A. Lasko CML 25 1 0 25 Nov 2021
ADCB: An Alzheimer's disease benchmark for evaluating observational estimators of causal effects N. M. Kinyanjui Fredrik D. Johansson CML 45 0 0 12 Nov 2021
Learning Pareto-Efficient Decisions with Confidence Sofia Ek Dave Zachariah Petre Stoica 8 1 0 19 Oct 2021
Conditional Cross-Design Synthesis Estimators for Generalizability in Medicaid Irina Degtiar T. Layton Jacob Wallace Sherri Rose CML 63 5 0 27 Sep 2021
Obtaining Causal Information by Merging Datasets with MAXENT Sergio Hernan Garrido Mejia Elke Kirschbaum Dominik Janzing CML 123 10 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 69 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 67 45 0 08 Apr 2021
Multi-Source Causal Inference Using Control Variates Wenshuo Guo S. Wang Peng Ding Yixin Wang Michael I. Jordan CML 101 19 0 30 Mar 2021
Causal Markov Boundaries Sofia Triantafillou Fattaneh Jabbari Gregory F. Cooper CML OOD 55 5 0 12 Mar 2021
A Review of Generalizability and Transportability Irina Degtiar Sherri Rose CML 53 220 0 23 Feb 2021
RealCause: Realistic Causal Inference Benchmarking Brady Neal Chin-Wei Huang Sunand Raghupathi CML ELM 72 34 0 30 Nov 2020
Causal Transfer Random Forest: Combining Logged Data and Randomized Experiments for Robust Prediction Shuxi Zeng Murat Ali Bayir Joel Pfeiffer Denis Xavier Charles Emre Kıcıman TTA 52 18 0 17 Oct 2020
How and Why to Use Experimental Data to Evaluate Methods for Observational Causal Inference A. Gentzel Purva Pruthi David D. Jensen CML 67 18 0 06 Oct 2020
Bandits with Partially Observable Confounded Data Guy Tennenholtz Uri Shalit Shie Mannor Yonathan Efroni OffRL 69 24 0 11 Jun 2020
Causal Inference With Selectively Deconfounded Data Kyra Gan Andrew A. Li Zachary Chase Lipton S. Tayur CML 61 7 0 25 Feb 2020
A Survey on Causal Inference Liuyi Yao Zhixuan Chu Sheng Li Yaliang Li Jing Gao Aidong Zhang CML 123 516 0 05 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 128 100 0 21 Jan 2020
Causal bootstrapping Max A. Little Reham Badawy CML 58 20 0 21 Oct 2019
Estimation of Personalized Heterogeneous Treatment Effects Using Concatenation and Augmentation of Feature Vectors Lev V. Utkin M. V. Kots V. Chukanov CML 43 1 0 09 Sep 2019
Policy Evaluation with Latent Confounders via Optimal Balance Andrew Bennett Nathan Kallus CML 62 18 0 06 Aug 2019
A Survey of Learning Causality with Data: Problems and Methods Ruocheng Guo Lu Cheng Jundong Li P. R. Hahn Huan Liu CML 88 168 0 25 Sep 2018