Bayesian Regression Trees
Bayesian Regression Trees is a probabilistic nonparametric regression model that uses a tree-based structure to partition the predictor space and assigns posterior distributions over tree configurations and leaf node parameters through Bayesian inference, distinguishing itself from classical regression trees by quantifying uncertainty in both structure and predictions.
102
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8.6K
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317
Authors
214
Institutions
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2017–2026
68
102
BART: Bayesian additive regression trees
The Annals of Applied Statistics · 2010 · 1.5K citations · Full text
BART: Bayesian Additive Regression Trees
ScholarlyCommons (University of Pennsylvania) · 2006 · 969 citations · Full text
D. Dension · Biometrika · 1998 · 320 citations
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University of Chicago
Chicago, United States
8 h-index
9 publications
1.4K citations
The University of Texas at Austin
Austin, United States
7 h-index
8 publications
1.6K citations

Medical College of Wisconsin
Milwaukee, United States
7 h-index
21 publications
1.1K citations
Arizona State University
Tempe, United States
6 h-index
7 publications
502 citations
University of Pennsylvania
Philadelphia, United States
5 h-index
6 publications
468 citations
Harvard University
Cambridge, United States
5 h-index
32 publications
615 citations

University of Salzburg
Salzburg, Austria
5 h-index
7 publications
296 citations
New York University
New York, United States
4 h-index
5 publications
282 citations
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8 publications · 466 citations
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5 publications · 451 citations
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4 publications · 129 citations
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4 publications · 193 citations
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Repository · 4 publications · 106 citations
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