Bayesian Time Series Classification
Bayesian Time Series Classification is a statistical classification framework that employs Bayesian inference to model uncertainty in time-dependent data sequences, distinguishing itself through the integration of prior knowledge and posterior updating within a probabilistic time series setting.
20
Publications
1.5K
Citations
79
Authors
43
Institutions
Publications per year
2017–2026
7
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1–5 of 20
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Consejo Nacional de Investigaciones Científicas y Técnicas, Argentina
1 publications · 792 citations
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1–5 of 79
43
University of Oxford
Oxford, United Kingdom
2 h-index
3 publications
856 citations
Institute of Applied Physics
Nizhny Novgorod, Russia
1 h-index
4 publications
80 citations
Major League Baseball
New York, United States
1 h-index
1 publications
792 citations
Google (Switzerland)
Zurich, Switzerland
1 h-index
1 publications
792 citations
Stony Brook University
Stony Brook, United States
1 h-index
1 publications
792 citations
Boston University
Boston, United States
1 h-index
1 publications
792 citations
OsloMet – Oslo Metropolitan University
Oslo, Norway
1 h-index
2 publications
22 citations
Politecnica Salesiana University
Cuenca, Ecuador
1 h-index
4 publications
552 citations
1–8 of 43
1 publications · 16 citations
1
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1 publications · 61 citations
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Repository · 1 publications · 15 citations
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1 publications · 13 citations
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1 publications · 792 citations
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