On the Testable Implications of Causal Models with Hidden Variables

12 December 2012

Papers citing "On the Testable Implications of Causal Models with Hidden Variables"

41 / 41 papers shown

Title
Testing Causal Models with Hidden Variables in Polynomial Delay via Conditional Independencies H. Jeong Adiba Ejaz Jin Tian Elias Bareinboim 58 2 0 22 Sep 2024
Consistency of Neural Causal Partial Identification Jiyuan Tan Jose Blanchet Vasilis Syrgkanis CML 109 0 0 24 May 2024
When does the ID algorithm fail? I. Shpitser CML 70 4 0 07 Jul 2023
Comparing Causal Frameworks: Potential Outcomes, Structural Models, Graphs, and Abstractions D. Ibeling Thomas Icard CML 75 10 0 25 Jun 2023
Learning Good Interventions in Causal Graphs via Covering Ayush Sawarni Rahul Madhavan Gaurav Sinha Siddharth Barman CML 41 4 0 08 May 2023
Causal Effect Identification in Uncertain Causal Networks S. Akbari Fatemeh Jamshidi Ehsan Mokhtarian M. Vowels Jalal Etesami Negar Kiyavash CML 63 3 0 09 Aug 2022
Graphical Representations for Algebraic Constraints of Linear Structural Equations Models T. V. Ommen Mathias Drton 86 1 0 01 Aug 2022
Negative Shannon Information Hides Networks Maohui Luo 45 0 0 09 Jun 2022
Experimental Design for Causal Effect Identification S. Akbari Jalal Etesami Negar Kiyavash CML 62 1 0 04 May 2022
Causal Effect Identification in Cluster DAGs Tarandeep Anand A. Ribeiro Jin Tian Elias Bareinboim CML 56 17 0 22 Feb 2022
An Automated Approach to Causal Inference in Discrete Settings Guilherme Duarte N. Finkelstein D. Knox Jonathan Mummolo I. Shpitser 96 49 0 28 Sep 2021
Restricted Hidden Cardinality Constraints in Causal Models Beata Zjawin Elie Wolfe Robert W. Spekkens CML 153 3 0 13 Sep 2021
The Proximal ID Algorithm I. Shpitser Zach Wood-Doughty E. T. Tchetgen CML 87 17 0 15 Aug 2021
Entropic Inequality Constraints from $e$ -separation Relations in Directed Acyclic Graphs with Hidden Variables N. Finkelstein Beata Zjawin Elie Wolfe I. Shpitser Robert W. Spekkens CML 63 3 0 15 Jul 2021
Nested Counterfactual Identification from Arbitrary Surrogate Experiments Juan D Correa Sanghack Lee Elias Bareinboim CML 65 36 0 07 Jul 2021
Differentiable Causal Discovery Under Unmeasured Confounding Rohit Bhattacharya Tushar Nagarajan Daniel Malinsky I. Shpitser CML 80 61 0 14 Oct 2020
Causal learning with sufficient statistics: an information bottleneck approach D. Chicharro M. Besserve S. Panzeri CML 65 5 0 12 Oct 2020
Path Dependent Structural Equation Models R. Srinivasan Jaron J. R. Lee Rohit Bhattacharya Narges Ahmidi I. Shpitser CML 63 4 0 24 Aug 2020
Semiparametric Inference For Causal Effects In Graphical Models With Hidden Variables Rohit Bhattacharya Razieh Nabi I. Shpitser CML 108 64 0 27 Mar 2020
Estimation of causal effects with small data in the presence of trapdoor variables Jouni Helske Santtu Tikka Juha Karvanen CML 34 9 0 06 Mar 2020
Efficient Distance Approximation for Structured High-Dimensional Distributions via Learning Arnab Bhattacharyya Sutanu Gayen Kuldeep S. Meel N. V. Vinodchandran 59 20 0 13 Feb 2020
Learning and Sampling of Atomic Interventions from Observations Arnab Bhattacharyya Sutanu Gayen S. Kandasamy Ashwin Maran N. V. Vinodchandran CML 59 4 0 11 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
Characterizing Distribution Equivalence and Structure Learning for Cyclic and Acyclic Directed Graphs AmirEmad Ghassami Alan Yang Negar Kiyavash Kun Zhang 81 2 0 28 Oct 2019
ASP-based Discovery of Semi-Markovian Causal Models under Weaker Assumptions Zhalama Zhalama Jiji Zhang F. Eberhardt W. Mayer Mark Junjie Li 37 7 0 06 Jun 2019
Algebraic Equivalence of Linear Structural Equation Models T. V. Ommen Joris M. Mooij 70 5 0 10 Jul 2018
Learning and Testing Causal Models with Interventions Jayadev Acharya Arnab Bhattacharyya C. Daskalakis S. Kandasamy CML 61 53 0 24 May 2018
The Inflation Technique Completely Solves the Causal Compatibility Problem M. Navascués Elie Wolfe 71 35 0 20 Jul 2017
Fair Inference On Outcomes Razieh Nabi I. Shpitser FaML 111 354 0 29 May 2017
Semidefinite tests for latent causal structures Aditya Kela Kai Von Prillwitz J. Åberg Rafael Chaves David Gross CML 91 19 0 03 Jan 2017
Causal inference via algebraic geometry: feasibility tests for functional causal structures with two binary observed variables Ciarán M. Gilligan-Lee Robert W. Spekkens CML 72 39 0 12 Jun 2015
Margins of discrete Bayesian networks R. Evans 106 69 0 09 Jan 2015
Graphs for margins of Bayesian networks R. Evans CML UQCV 121 92 0 08 Aug 2014
Inferring latent structures via information inequalities Rafael Chaves L. Luft T. O. Maciel David Gross Dominik Janzing Bernhard Schölkopf CML 149 43 0 08 Jul 2014
Graphical methods for inequality constraints in marginalized DAGs R. Evans CML 126 42 0 13 Sep 2012
A theoretical study of Y structures for causal discovery S. Mani Peter Spirtes G. Cooper CML 115 64 0 27 Jun 2012
Pearl's Calculus of Intervention Is Complete Yimin Huang Marco Valtorta CML 107 232 0 27 Jun 2012
Inequality Constraints in Causal Models with Hidden Variables Changsung Kang Jin Tian 83 33 0 27 Jun 2012
Polynomial Constraints in Causal Bayesian Networks Changsung Kang Jin Tian TPM 105 12 0 20 Jun 2012
Counterfactual Graphical Models for Longitudinal Mediation Analysis with Unobserved Confounding I. Shpitser AI4CE 117 107 0 01 May 2012
A Sequence of Relaxations Constraining Hidden Variable Models Greg Ver Steeg Aram Galstyan 176 21 0 08 Jun 2011