Bayesian Change-point Detection
Bayesian Change-Point Detection is a statistical methodology within sequential Bayesian inference that identifies abrupt changes in the generative parameters of a time series through probabilistic updating of change-point occurrences using prior-to-posterior belief propagation.
262
Publications
13.4K
Citations
659
Authors
376
Institutions
Publications per year
2017–2026
68
Variants
Bayesian Change Point Detection
262
Bayesian Online Changepoint Detection
Ryan P. Adams, David Mackay · ArXiv.org · 2007 · 603 citations · Full text
Kaiguang Zhao, Michael A. Wulder, Tongxi Hu et al. · Remote Sensing of Environment · 2019 · 481 citations · Full text
U. von Toussaint · Reviews of Modern Physics · 2011 · 435 citations · Full text
On Tests for Detecting Change in Mean
Ashish Sen, Muni S. Srivastava · The Annals of Statistics · 1975 · 357 citations · Full text
1–5 of 262
659
Institut National de la Recherche Scientifique, Canada
5 publications · 223 citations
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University of Southern California, United States
4 publications · 352 citations
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376

Institut National de la Recherche Scientifique
Québec, Canada
9 h-index
21 publications
1.5K citations
University of California, Los Angeles
Los Angeles, United States
6 h-index
16 publications
477 citations
University of Oxford
Oxford, United Kingdom
5 h-index
14 publications
859 citations
Natural Sciences and Engineering Research Council of Canada
Ottawa, Canada
5 h-index
12 publications
1.1K citations

Imperial College London
London, United Kingdom
5 h-index
5 publications
373 citations
Hydro-Québec
Montreal, Canada
5 h-index
12 publications
1.1K citations
University of Cambridge
Cambridge, United Kingdom
5 h-index
12 publications
527 citations
University of Michigan
Ann Arbor, United States
4 h-index
8 publications
422 citations
1–8 of 376
6 publications · 327 citations
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Repository · 6 publications · 114 citations
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5 publications · 238 citations
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5 publications · 239 citations
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5 publications · 1K citations
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