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Efficient adjustment sets in causal graphical models with hidden
  variables
v1v2v3 (latest)

Efficient adjustment sets in causal graphical models with hidden variables

22 April 2020
Ezequiel Smucler
F. Sapienza
A. Rotnitzky
    CMLOffRL
ArXiv (abs)PDFHTML

Papers citing "Efficient adjustment sets in causal graphical models with hidden variables"

15 / 15 papers shown
Title
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
Spatio-Temporal Graphical Counterfactuals: An Overview
Spatio-Temporal Graphical Counterfactuals: An Overview
Mingyu Kang
Duxin Chen
Ziyuan Pu
Jianxi Gao
Wenwu Yu
CML
107
1
0
02 Jul 2024
A Review of Off-Policy Evaluation in Reinforcement Learning
A Review of Off-Policy Evaluation in Reinforcement Learning
Masatoshi Uehara
C. Shi
Nathan Kallus
OffRL
102
76
0
13 Dec 2022
Finding and Listing Front-door Adjustment Sets
Finding and Listing Front-door Adjustment Sets
H. Jeong
Jin Tian
Elias Bareinboim
79
9
0
11 Oct 2022
Graphical tools for selecting conditional instrumental sets
Graphical tools for selecting conditional instrumental sets
Leonard Henckel
Martin Buttenschon
Marloes H. Maathuis
CML
84
9
0
07 Aug 2022
Variable elimination, graph reduction and efficient g-formula
Variable elimination, graph reduction and efficient g-formula
F. R. Guo
Emilija Perković
A. Rotnitzky
CML
74
7
0
24 Feb 2022
A note on efficient minimum cost adjustment sets in causal graphical
  models
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
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
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
Causal Markov Boundaries
Sofia Triantafillou
Fattaneh Jabbari
Gregory F. Cooper
CMLOOD
55
5
0
12 Mar 2021
Incorporating Causal Graphical Prior Knowledge into Predictive Modeling
  via Simple Data Augmentation
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
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
Efficient least squares for estimating total effects under linearity and
  causal sufficiency
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
On efficient adjustment in causal graphs
On efficient adjustment in causal graphs
Jan-Jelle Witte
Leonard Henckel
Marloes H. Maathuis
Vanessa Didelez
CML
80
70
0
17 Feb 2020
Graphical Criteria for Efficient Total Effect Estimation via Adjustment
  in Causal Linear Models
Graphical Criteria for Efficient Total Effect Estimation via Adjustment in Causal Linear Models
Leonard Henckel
Emilija Perković
Marloes H. Maathuis
CML
104
108
0
04 Jul 2019
1