Constraint-based Structure Learning
Constraint-Based Structure Learning is a method for inferring the structure of a Directed Acyclic Graph by identifying conditional independence relationships among variables to constrain the space of possible graphical models.
45
Publications
2.5K
Citations
105
Authors
59
Institutions
Publications per year
2017–2026
15
Parents
45
Causal Discovery for Climate Research Using Graphical Models
Imme Ebert‐Uphoff, Yi Deng · Journal of Climate · 2012 · 194 citations · Full text
Structured learning with constrained conditional models
Ming‐Wei Chang, Lev Ratinov, Dan Roth · Machine Learning · 2012 · 126 citations · Full text
1–5 of 45
105
Dalle Molle Institute for Artificial Intelligence Research, Switzerland
4 publications · 238 citations
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2
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2
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2
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1–5 of 105
59
Georgia Institute of Technology
Atlanta, United States
4 h-index
8 publications
291 citations
University of Oxford
Oxford, United Kingdom
3 h-index
3 publications
192 citations
ETH Zurich
Zurich, Switzerland
3 h-index
6 publications
1.1K citations

Griffith University
Brisbane, Australia
2 h-index
2 publications
30 citations
Aalto University
Espoo, Finland
2 h-index
5 publications
72 citations

University of Helsinki
Helsinki, Finland
2 h-index
2 publications
30 citations
Åbo Akademi University
Turku, Finland
2 h-index
4 publications
60 citations
Carnegie Mellon University
Pittsburgh, United States
2 h-index
2 publications
78 citations
1–8 of 59
Repository · 6 publications · 584 citations
6
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1 publications · 119 citations
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JSS · 1 publications · 149 citations
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AAI · 1 publications · 47 citations
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Conference · 1 publications · 12 citations
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