Keyword

d-separation

Description: A graphical criterion in causal inference that determines conditional independence between variables in a directed acyclic graph.

Primary topic: Bayesian Modeling and Causal Inference (76%)

OpenAlex ID: keywords/d-separation

Context-Specific Independence in Bayesian Networks

2013 · Boutilier, Craig, Friedman, Nir, et al. · arXiv (Cornell University) · 568

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Identifying independence in bayesian networks

1990 · Dan Geiger, Thomas Verma, et al. · Networks · 513

A New Inferential Test for Path Models Based on Directed Acyclic Graphs

2000 · Bill Shipley · Structural Equation Modeling A Multidisciplinary Journal · 490

Causal Networks: Semantics and Expressiveness

1990 · Thomas VERMA, Judea PEARL · Machine intelligence and pattern recognition · 357

Credal networks

2000 · Fabio G. Cozman · Artificial Intelligence · 343

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Graphical Causal Models

2013 · Felix Elwert · Handbooks of sociology and social research · 325

An Algorithm for Deciding if a Set of Observed Independencies Has a Causal Explanation

1992 · Thomas Verma, Judea Pearl · Uncertainty in Artificial Intelligence · 234

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Strong Completeness and Faithfulness in Bayesian Networks

2013 · Meek, Christopher · arXiv (Cornell University) · 194

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Theory-independent limits on correlations from generalized Bayesian networks

2014 · Joe Henson, Raymond Lal, et al. · New Journal of Physics · 191

Markov Properties for Acyclic Directed Mixed Graphs

2003 · THOMAS RICHARDSON · Scandinavian Journal of Statistics · 189

d-Separation: From Theorems to Algorithms

2013 · Geiger, Dan, Verma, Tom S., et al. · arXiv (Cornell University) · 180

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Learning the Structure of Linear Latent Variable Models

2018 · Silva, Ricardo, Scheines, Richard, et al. · 172

Improving Bayesian Network Structure Learning with Mutual Information-Based Node Ordering in the K2 Algorithm

2008 · Xue-Wen Chen, Gopalakrishna Anantha, et al. · IEEE Transactions on Knowledge and Data Engineering · 165

An Introduction to Phylogenetic Path Analysis

2014 · Alejandro Gonzalez-Voyer, Achaz von Hardenberg · Springer eBooks · 117

Edge-Cut Bounds on Network Coding Rates

2006 · Gerhard Kramer, Serap A. Savari · Journal of Network and Systems Management · 109

A new approach for learning belief networks using independence criteria

2000 · Luis M. de Campos, Juan F. Huete · International Journal of Approximate Reasoning · 109

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On the Logic of Causal Models

1990 · Dan GEIGER, Judea PEARL · Machine intelligence and pattern recognition · 106

Causal Networks: Semantics and Expressiveness

2013 · Verma, Tom S., Pearl, Judea · arXiv (Cornell University) · 102

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Pearl's D-Separation: One More Step Into Causal Thinking

2003 · Leslie Hayduk, Greta Cummings, et al. · Structural Equation Modeling A Multidisciplinary Journal · 102

A graph-separation theorem for quantum causal models

2015 · Jacques Pienaar, Časlav Brukner · New Journal of Physics · 82

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Trek Separation for Gaussian Graphical Models

2008 · Sullivant, S, Talaska, K, et al. · Centrum Wiskunde & Informatica (CWI), the national research institute for mathematics and computer science in the Netherlands · 76

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Generating Bayesian Networks from Probability Logic Knowledge Bases

1994 · Peter Haddawy · Elsevier eBooks · 76

A Review of Bayesian Networks and Structure Learning

2012 · John Noble, Timo J.T. Koski · Roczniki Polskiego Towarzystwa Matematycznego. Seria 3, Matematyka Stosowana/Matematyka Stosowana/Mathematica Applicanda · 75

Local fit evaluation of structural equation models using graphical criteria.

2017 · Felix Thoemmes, Yves Rosseel, et al. · Psychological Methods · 70

On the Validity of the Markov Interpretation of Path Diagrams of Gaussian Structural Equations Systems with Correlated Errors

1999 · Jan T. A. Koster · Scandinavian Journal of Statistics · 70

Works count: 423

Citation count: 7,551