Markov Equivalence
Mark Equivalence is a theoretical construct in the domain of causal graphical models that designates a set of directed acyclic graphs which encode the same conditional independence relations among variables, thereby being indistinguishable based on observational data alone.
80
Publications
4K
Citations
126
Authors
69
Institutions
Publications per year
2017–2026
28
Variants
Markov Equivalence Class
80
Causal discovery with continuous additive noise models
Jonas Peters, Joris M. Mooij, Dominik Janzing et al. · Journal of Machine Learning Research · 2014 · 284 citations
1–5 of 80
126
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69
University of Washington
Seattle, United States
10 h-index
19 publications
2.8K citations
Carnegie Mellon University
Pittsburgh, United States
7 h-index
11 publications
488 citations
ETH Zurich
Zurich, Switzerland
6 h-index
9 publications
1.3K citations
Massachusetts Institute of Technology
Cambridge, United States
4 h-index
8 publications
122 citations
Max Planck Society
Munich, Germany
4 h-index
8 publications
1.3K citations

Università Cattolica del Sacro Cuore
Milan, Italy
4 h-index
11 publications
243 citations

Radboud University Nijmegen
Nijmegen, The Netherlands
3 h-index
3 publications
504 citations
University of Pennsylvania
Philadelphia, United States
3 h-index
4 publications
63 citations
1–8 of 69
Repository · 15 publications · 628 citations
12
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6 publications · 636 citations
6
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Conference · 4 publications · 75 citations
4
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4 publications · 338 citations
4
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Repository · 2 publications · 23 citations
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1–5