Hidden Markov Models
Hidden Markov Model is a stochastic process in which a sequence of observable events depends on an underlying, unobservable Markov process with a finite number of states, distinguishing it from other probabilistic models by the assumption that the system being modeled is a Markov process with hidden states and probabilistic emissions.
7.9K
Publications
521K
Citations
15.5K
Authors
3.2K
Institutions
Publications per year
2017–2026
1.3K
Variants
Hidden Markov ModelHmmHmms
7.9K
Accelerated Profile HMM Searches
Sean R. Eddy · PLoS Computational Biology · 2011 · 7.5K citations · Full text
1–5 of 7.9K
15.5K
26
h-index
25
h-index
24
h-index
23
h-index
Centre National de la Recherche Scientifique, France
38 publications · 1.6K citations
22
h-index
1–5 of 15.5K
3.2K
AT&T (United States)
Bedminster, United States
61 h-index
238 publications
55.8K citations

Centre National de la Recherche Scientifique
Paris, France
46 h-index
353 publications
19.2K citations
Carnegie Mellon University
Pittsburgh, United States
45 h-index
214 publications
28.6K citations
University of Cambridge
Cambridge, United Kingdom
43 h-index
209 publications
25.8K citations
University of California, Berkeley
Berkeley, United States
42 h-index
150 publications
13.6K citations
Massachusetts Institute of Technology
Cambridge, United States
40 h-index
160 publications
17.6K citations
University of Washington
Seattle, United States
39 h-index
167 publications
15.2K citations
Georgia Institute of Technology
Atlanta, United States
35 h-index
183 publications
9K citations
1–8 of 3.2K
107 publications · 7.8K citations
48
h-index
TPAMI · 79 publications · 13.7K citations
48
h-index
113 publications · 10.5K citations
46
h-index
81 publications · 7.4K citations
41
h-index
79 publications · 4.7K citations
40
h-index
1–5