Variable-length Hidden Markov Models
Variable-Length Hidden Markov Models is a type of probabilistic sequence model that extends the standard Hidden Markov Model by allowing state durations to follow variable-length distributions, thereby capturing temporal dependencies with non-geometric duration densities.
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2.7K
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2017–2026
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Variable-length HmmsVlhmm
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University of Manchester
Manchester, United Kingdom
6 h-index
20 publications
607 citations
Georgia Institute of Technology
Atlanta, United States
4 h-index
13 publications
318 citations

University of Leeds
Leeds, United Kingdom
3 h-index
7 publications
896 citations
Universidade de São Paulo
São Paulo, Brazil
2 h-index
10 publications
415 citations
Microsoft Research Asia (China)
Beijing, China
2 h-index
3 publications
235 citations
Simon Fraser University
Burnaby, Canada
2 h-index
2 publications
123 citations
Rochester Institute of Technology
Rochester, United States
2 h-index
5 publications
105 citations
University of California, Berkeley
Berkeley, United States
2 h-index
6 publications
339 citations
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CVIU · 2 publications · 287 citations
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2 publications · 28 citations
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2 publications · 50 citations
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2 publications · 69 citations
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2 publications · 122 citations
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