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Graphical Criteria for Efficient Total Effect Estimation via Adjustment in Causal Linear Models

4 July 2019

Papers citing "Graphical Criteria for Efficient Total Effect Estimation via Adjustment in Causal Linear Models"

47 / 47 papers shown

Title
Linear-Time Primitives for Algorithm Development in Graphical Causal Inference Marcel Wienöbst Sebastian Weichwald Leonard Henckel 12 0 0 18 Jun 2025
Causal Effect Identification in lvLiNGAM from Higher-Order Cumulants D. Tramontano Yaroslav Kivva Saber Salehkaleybar Mathias Drton Negar Kiyavash CML 105 0 0 05 Jun 2025
Your Assumed DAG is Wrong and Here's How To Deal With It Kirtan Padh Zhufeng Li Cecilia Casolo Niki Kilbertus CML 104 0 0 24 Feb 2025
SNAP: Sequential Non-Ancestor Pruning for Targeted Causal Effect Estimation With an Unknown Graph Mátyás Schubert Tom Claassen Sara Magliacane CML 112 0 0 11 Feb 2025
Practically Effective Adjustment Variable Selection in Causal Inference Atsushi Noda Takashi Isozaki 117 0 0 04 Feb 2025
Local Learning for Covariate Selection in Nonparametric Causal Effect Estimation with Latent Variables Zheng Li Feng Xie Xichen Guo Yan Zeng Hao Zhang Zhi Geng CML 212 0 0 25 Nov 2024
Identifying Total Causal Effects in Linear Models under Partial Homoscedasticity David Strieder Mathias Drton CML 54 0 0 12 Aug 2024
A matrix algebra for graphical statistical models Qingyuan Zhao 68 1 0 22 Jul 2024
Fast Proxy Experiment Design for Causal Effect Identification Sepehr Elahi S. Akbari Jalal Etesami Negar Kiyavash Patrick Thiran 55 0 0 07 Jul 2024
Neural Networks with Causal Graph Constraints: A New Approach for Treatment Effects Estimation Roger Pros Jordi Vitrià CML 90 0 0 18 Apr 2024
Faithlessness in Gaussian graphical models Mathias Drton Leonard Henckel Benjamin Hollering Pratik Misra 73 1 0 08 Apr 2024
Disparate Effect Of Missing Mediators On Transportability of Causal Effects Vishwali Mhasawade R. Chunara 40 0 0 13 Mar 2024
Efficient adjustment for complex covariates: Gaining efficiency with DOPE Alexander Mangulad Christgau Niels Richard Hansen 93 3 0 20 Feb 2024
Adjustment Identification Distance: A gadjid for Causal Structure Learning Leonard Henckel Theo Würtzen Sebastian Weichwald CML 100 11 0 13 Feb 2024
Bayesian Causal Inference with Gaussian Process Networks Enrico Giudice Jack Kuipers G. Moffa 73 1 0 01 Feb 2024
Confounder selection via iterative graph expansion F. R. Guo Qingyuan Zhao CML 40 6 0 12 Sep 2023
Joint structure learning and causal effect estimation for categorical graphical models F. Castelletti G. Consonni Marco L. Della Vedova CML 50 2 0 28 Jun 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 28 0 0 09 Jun 2023
Do we become wiser with time? On causal equivalence with tiered background knowledge Christine W. Bang Vanessa Didelez 61 3 0 02 Jun 2023
Toward Falsifying Causal Graphs Using a Permutation-Based Test Elias Eulig Atalanti A. Mastakouri Patrick Blobaum Michael W. Hardt Dominik Janzing 35 13 0 16 May 2023
Local Causal Discovery for Estimating Causal Effects Shantanu Gupta David Benjamin Childers Zachary Chase Lipton CML 70 12 0 16 Feb 2023
Data-Driven Estimation of Heterogeneous Treatment Effects Christopher Tran Keith Burghardt Kristina Lerman Elena Zheleva CML 56 1 0 16 Jan 2023
Confounder Selection: Objectives and Approaches F. R. Guo A. Lundborg Qingyuan Zhao CML 59 6 0 29 Aug 2022
Data-Driven Causal Effect Estimation Based on Graphical Causal Modelling: A Survey Debo Cheng Jiuyong Li Lin Liu Jixue Liu T. Le CML 94 32 0 20 Aug 2022
Valid Inference after Causal Discovery Paula Gradu Tijana Zrnic Yixin Wang Michael I. Jordan CML 81 8 0 11 Aug 2022
Graphical tools for selecting conditional instrumental sets Leonard Henckel Martin Buttenschon Marloes H. Maathuis CML 84 9 0 07 Aug 2022
On the Representation of Causal Background Knowledge and its Applications in Causal Inference Zhuangyan Fang Ruiqi Zhao Yue Liu Yangbo He 72 4 0 10 Jul 2022
Improving Data-driven Heterogeneous Treatment Effect Estimation Under Structure Uncertainty Christopher Tran Elena Zheleva CML 70 4 0 25 Jun 2022
Variable elimination, graph reduction and efficient g-formula F. R. Guo Emilija Perković A. Rotnitzky CML 74 7 0 24 Feb 2022
A Free Lunch with Influence Functions? Improving Neural Network Estimates with Concepts from Semiparametric Statistics M. Vowels S. Akbari Necati Cihan Camgöz Richard Bowden 60 4 0 18 Feb 2022
Sequentially learning the topological ordering of causal directed acyclic graphs with likelihood ratio scores Gabriel Ruiz Oscar Hernan Madrid Padilla Qing Zhou CML 68 2 0 03 Feb 2022
A note on efficient minimum cost adjustment sets in causal graphical models Ezequiel Smucler A. Rotnitzky CML 60 8 0 06 Jan 2022
Leveraging Causal Graphs for Blocking in Randomized Experiments A. Umrawal CML 51 0 0 03 Nov 2021
Efficient Online Estimation of Causal Effects by Deciding What to Observe Shantanu Gupta Zachary Chase Lipton David Benjamin Childers CML 83 19 0 20 Aug 2021
Causal Markov Boundaries Sofia Triantafillou Fattaneh Jabbari Gregory F. Cooper CML OOD 55 5 0 12 Mar 2021
Incorporating Causal Graphical Prior Knowledge into Predictive Modeling via Simple Data Augmentation Takeshi Teshima Masashi Sugiyama CML 86 13 0 27 Feb 2021
Necessary and sufficient graphical conditions for optimal adjustment sets in causal graphical models with hidden variables Jakob Runge CML 94 27 0 20 Feb 2021
Minimal enumeration of all possible total effects in a Markov equivalence class F. R. Guo Emilija Perković CML 38 17 0 16 Oct 2020
Efficient least squares for estimating total effects under linearity and causal sufficiency By F. Richard Guo Emilija Perković CML 109 13 0 08 Aug 2020
Learning Adjustment Sets from Observational and Limited Experimental Data Sofia Triantafillou Gregory F. Cooper CML 43 7 0 18 May 2020
Efficient adjustment sets in causal graphical models with hidden variables Ezequiel Smucler F. Sapienza A. Rotnitzky CML OffRL 95 33 0 22 Apr 2020
The Variance of Causal Effect Estimators for Binary V-structures Jack Kuipers G. Moffa CML 42 6 0 20 Apr 2020
Semiparametric Inference For Causal Effects In Graphical Models With Hidden Variables Rohit Bhattacharya Razieh Nabi I. Shpitser CML 96 64 0 27 Mar 2020
Estimating Treatment Effects with Observed Confounders and Mediators Shantanu Gupta Zachary Chase Lipton David Benjamin Childers CML 68 17 0 26 Mar 2020
On efficient adjustment in causal graphs Jan-Jelle Witte Leonard Henckel Marloes H. Maathuis Vanessa Didelez CML 80 70 0 17 Feb 2020
Efficient adjustment sets for population average treatment effect estimation in non-parametric causal graphical models A. Rotnitzky Ezequiel Smucler CML 96 31 0 01 Dec 2019
Identifying causal effects in maximally oriented partially directed acyclic graphs Emilija Perković CML 59 39 0 07 Oct 2019