Multiple Change-point Detection
Multiple Change-Point Detection is a statistical inference method that identifies more than one point in an ordered sequence of data where abrupt changes occur in the underlying generative process, distinguishing itself from single change-point detection by enabling the simultaneous localization of multiple such transitions.
199
Publications
14.2K
Citations
396
Authors
276
Institutions
Publications per year
2017–2026
67
Parents
199
1–5 of 199
396
London School of Economics and Political Science, United Kingdom
10 publications · 517 citations
10
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5
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5
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4
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4
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1–5 of 396
276
London School of Economics and Political Science
London, United Kingdom
12 h-index
15 publications
1.3K citations
University of California, Los Angeles
Los Angeles, United States
7 h-index
11 publications
750 citations
Université Paris-Sud
Orsay, France
7 h-index
8 publications
1K citations
Mississippi State University
Starkville, United States
5 h-index
5 publications
257 citations
Iowa State University
Ames, United States
5 h-index
7 publications
465 citations
Université Paris Cité
Paris, France
5 h-index
5 publications
676 citations
Yale University
New Haven, United States
5 h-index
10 publications
335 citations

Centre National de la Recherche Scientifique
Paris, France
5 h-index
9 publications
537 citations
1–8 of 276
Repository · 14 publications · 741 citations
12
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7 publications · 1.2K citations
7
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CSDA · 6 publications · 238 citations
6
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JSS · 3 publications · 1.7K citations
4
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4 publications · 132 citations
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