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1907.02435
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Graphical Criteria for Efficient Total Effect Estimation via Adjustment in Causal Linear Models
4 July 2019
Leonard Henckel
Emilija Perković
Marloes H. Maathuis
CML
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Papers citing
"Graphical Criteria for Efficient Total Effect Estimation via Adjustment in Causal Linear Models"
48 / 48 papers shown
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SNAP: Sequential Non-Ancestor Pruning for Targeted Causal Effect Estimation With an Unknown Graph
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318
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Practically Effective Adjustment Variable Selection in Causal Inference
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Local Learning for Covariate Selection in Nonparametric Causal Effect Estimation with Latent Variables
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Identifying Total Causal Effects in Linear Models under Partial Homoscedasticity
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Mathias Drton
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248
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A matrix algebra for graphical statistical models
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248
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Fast Proxy Experiment Design for Causal Effect Identification
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231
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Neural Networks with Causal Graph Constraints: A New Approach for Treatment Effects Estimation
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Jordi Vitrià
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304
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Faithlessness in Gaussian graphical models
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Leonard Henckel
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Pratik Misra
303
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Disparate Effect Of Missing Mediators On Transportability of Causal Effects
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155
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13 Mar 2024
Efficient adjustment for complex covariates: Gaining efficiency with DOPE
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Niels Richard Hansen
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349
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20 Feb 2024
Adjustment Identification Distance: A gadjid for Causal Structure Learning
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Theo Würtzen
Sebastian Weichwald
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13 Feb 2024
Bayesian Causal Inference with Gaussian Process Networks
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Jack Kuipers
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Confounder selection via iterative graph expansion
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Qingyuan Zhao
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272
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12 Sep 2023
Joint structure learning and causal effect estimation for categorical graphical models
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F. Castelletti
G. Consonni
Marco L. Della Vedova
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179
4
0
28 Jun 2023
Causal Effect Estimation from Observational and Interventional Data Through Matrix Weighted Linear Estimators
Conference on Uncertainty in Artificial Intelligence (UAI), 2023
Klaus-Rudolf Kladny
Julius von Kügelgen
Bernhard Schölkopf
Michael Muehlebach
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234
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09 Jun 2023
Do we become wiser with time? On causal equivalence with tiered background knowledge
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Christine W. Bang
Vanessa Didelez
277
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Toward Falsifying Causal Graphs Using a Permutation-Based Test
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Elias Eulig
Atalanti A. Mastakouri
Patrick Blobaum
Michael W. Hardt
Dominik Janzing
196
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0
16 May 2023
Local Causal Discovery for Estimating Causal Effects
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Shantanu Gupta
David Benjamin Childers
Zachary Chase Lipton
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621
16
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16 Feb 2023
Data-Driven Estimation of Heterogeneous Treatment Effects
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Keith Burghardt
Kristina Lerman
Elena Zheleva
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256
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16 Jan 2023
Confounder Selection: Objectives and Approaches
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Qingyuan Zhao
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352
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29 Aug 2022
Data-Driven Causal Effect Estimation Based on Graphical Causal Modelling: A Survey
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Debo Cheng
Jiuyong Li
Lin Liu
Jixue Liu
T. Le
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394
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20 Aug 2022
Valid Inference after Causal Discovery
Journal of the American Statistical Association (JASA), 2022
Paula Gradu
Tijana Zrnic
Yixin Wang
Michael I. Jordan
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459
17
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11 Aug 2022
Graphical tools for selecting conditional instrumental sets
Leonard Henckel
Martin Buttenschon
Marloes H. Maathuis
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441
12
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07 Aug 2022
On the Representation of Pairwise Causal Background Knowledge and Its Applications in Causal Inference
Zhuangyan Fang
Ruiqi Zhao
Yue Liu
Yangbo He
295
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10 Jul 2022
Improving Data-driven Heterogeneous Treatment Effect Estimation Under Structure Uncertainty
Knowledge Discovery and Data Mining (KDD), 2022
Christopher Tran
Elena Zheleva
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327
4
0
25 Jun 2022
Variable elimination, graph reduction and efficient g-formula
Biometrika (Biometrika), 2022
F. R. Guo
Emilija Perković
A. Rotnitzky
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495
10
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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
293
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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
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304
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03 Feb 2022
A note on efficient minimum cost adjustment sets in causal graphical models
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Ezequiel Smucler
A. Rotnitzky
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252
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06 Jan 2022
Leveraging Causal Graphs for Blocking in Randomized Experiments
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A. Umrawal
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276
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Efficient Online Estimation of Causal Effects by Deciding What to Observe
Shantanu Gupta
Zachary Chase Lipton
David Benjamin Childers
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456
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20 Aug 2021
Causal Markov Boundaries
Sofia Triantafillou
Fattaneh Jabbari
Gregory F. Cooper
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226
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Incorporating Causal Graphical Prior Knowledge into Predictive Modeling via Simple Data Augmentation
Conference on Uncertainty in Artificial Intelligence (UAI), 2021
Takeshi Teshima
Masashi Sugiyama
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522
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27 Feb 2021
Necessary and sufficient graphical conditions for optimal adjustment sets in causal graphical models with hidden variables
Neural Information Processing Systems (NeurIPS), 2021
Jakob Runge
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502
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20 Feb 2021
Minimal enumeration of all possible total effects in a Markov equivalence class
International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
F. R. Guo
Emilija Perković
CML
442
15
0
16 Oct 2020
Efficient least squares for estimating total effects under linearity and causal sufficiency
Journal of machine learning research (JMLR), 2020
By F. Richard Guo
Emilija Perković
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478
15
0
08 Aug 2020
Learning Adjustment Sets from Observational and Limited Experimental Data
Sofia Triantafillou
Gregory F. Cooper
CML
233
7
0
18 May 2020
Efficient adjustment sets in causal graphical models with hidden variables
Ezequiel Smucler
F. Sapienza
A. Rotnitzky
CML
OffRL
464
37
0
22 Apr 2020
The Variance of Causal Effect Estimators for Binary V-structures
Journal of Causal Inference (JCI), 2020
Jack Kuipers
G. Moffa
CML
245
7
0
20 Apr 2020
Semiparametric Inference For Causal Effects In Graphical Models With Hidden Variables
Journal of machine learning research (JMLR), 2020
Rohit Bhattacharya
Razieh Nabi
I. Shpitser
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467
69
0
27 Mar 2020
Estimating Treatment Effects with Observed Confounders and Mediators
Conference on Uncertainty in Artificial Intelligence (UAI), 2020
Shantanu Gupta
Zachary Chase Lipton
David Benjamin Childers
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335
19
0
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On efficient adjustment in causal graphs
Jan-Jelle Witte
Leonard Henckel
Marloes H. Maathuis
Vanessa Didelez
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425
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Efficient adjustment sets for population average treatment effect estimation in non-parametric causal graphical models
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Ezequiel Smucler
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315
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0
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Identifying causal effects in maximally oriented partially directed acyclic graphs
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Emilija Perković
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308
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