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Margins of discrete Bayesian networks

9 January 2015

Papers citing "Margins of discrete Bayesian networks"

31 / 31 papers shown

Title
Deriving Causal Order from Single-Variable Interventions: Guarantees & Algorithm Mathieu Chevalley Patrick Schwab Arash Mehrjou 141 1 0 28 May 2024
When does the ID algorithm fail? I. Shpitser CML 62 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
Supermodular Rank: Set Function Decomposition and Optimization Rishi Sonthalia A. Seigal Guido Montúfar LRM 38 1 0 24 May 2023
A Layered Architecture for Universal Causality Sridhar Mahadevan AI4CE 48 0 0 18 Dec 2022
On the Complexity of Counterfactual Reasoning Yunqiu Han Yizuo Chen Adnan Darwiche 62 7 0 24 Nov 2022
Causal Discovery in Linear Latent Variable Models Subject to Measurement Error Yuqin Yang AmirEmad Ghassami M. Nafea Negar Kiyavash Kun Zhang I. Shpitser CML 45 8 0 08 Nov 2022
Unifying Causal Inference and Reinforcement Learning using Higher-Order Category Theory Sridhar Mahadevan 51 4 0 13 Sep 2022
On The Universality of Diagrams for Causal Inference and The Causal Reproducing Property Sridhar Mahadevan 70 5 0 06 Jul 2022
Causal Structure Learning: a Combinatorial Perspective C. Squires Caroline Uhler CML 120 47 0 02 Jun 2022
On Testability of the Front-Door Model via Verma Constraints Rohit Bhattacharya Razieh Nabi 85 9 0 01 Mar 2022
Variable elimination, graph reduction and efficient g-formula F. R. Guo Emilija Perković A. Rotnitzky CML 74 7 0 24 Feb 2022
Partial Counterfactual Identification from Observational and Experimental Data Junzhe Zhang Jin Tian Elias Bareinboim 71 64 0 12 Oct 2021
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
Causal Homotopy Sridhar Mahadevan CML 44 6 0 20 Sep 2021
Learning latent causal graphs via mixture oracles Bohdan Kivva Goutham Rajendran Pradeep Ravikumar Bryon Aragam CML 82 48 0 29 Jun 2021
Partial Identifiability in Discrete Data With Measurement Error N. Finkelstein R. Adams Suchi Saria I. Shpitser 75 11 0 23 Dec 2020
Differentiable Causal Discovery Under Unmeasured Confounding Rohit Bhattacharya Tushar Nagarajan Daniel Malinsky I. Shpitser CML 80 61 0 14 Oct 2020
Faster algorithms for Markov equivalence Zhongyi Hu R. Evans 82 12 0 05 Jul 2020
Full Law Identification In Graphical Models Of Missing Data: Completeness Results Razieh Nabi Rohit Bhattacharya I. Shpitser 61 50 0 10 Apr 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
Causality-based Feature Selection: Methods and Evaluations Kui Yu Xianjie Guo Lin Liu Jiuyong Li Hao Wang Zhaolong Ling Xindong Wu CML 92 97 0 17 Nov 2019
Quantum Inflation: A General Approach to Quantum Causal Compatibility Elie Wolfe Alejandro Pozas-Kerstjens Matan Grinberg D. Rosset A. Acín M. Navascués AI4CE 92 56 0 23 Sep 2019
Towards Characterising Bayesian Network Models under Selection A. Armen R. Evans CML 61 1 0 13 Nov 2018
Algebraic Equivalence of Linear Structural Equation Models T. V. Ommen Joris M. Mooij 70 5 0 10 Jul 2018
Constraint-based Causal Discovery for Non-Linear Structural Causal Models with Cycles and Latent Confounders Patrick Forré Joris M. Mooij CML 92 56 0 09 Jul 2018
The Inflation Technique Completely Solves the Causal Compatibility Problem M. Navascués Elie Wolfe 71 35 0 20 Jul 2017
Algebraic Problems in Structural Equation Modeling Mathias Drton 72 48 0 18 Dec 2016
Foundations of Structural Causal Models with Cycles and Latent Variables Stephan Bongers Patrick Forré J. Peters Joris M. Mooij 95 167 0 18 Nov 2016
Smooth, identifiable supermodels of discrete DAG models with latent variables R. Evans Thomas S. Richardson CML 64 22 0 21 Nov 2015