First-Order Markov Models is a stochastic process model in which the future state depends exclusively on the current state, embodying the Markov property of memorylessness with a single-step dependency structure.
486
Publications
28.3K
Citations
1.1K
Authors
562
Institutions
Publications per year
2017–2026
44
Variants
First-order Markov Chains
Parents
Publications
486
Phase Unwrapping via Graph Cuts
José M. Bioucas‐Dias, Gonalo Valadao · IEEE Transactions on Image Processing · 2007 · 566 citations
Modeling Online Browsing and Path Analysis Using Clickstream Data
Alan L. Montgomery, Shibo Li, Kannan Srinivasan et al. · Marketing Science · 2004 · 565 citations
1–5 of 486
Authors
1.1K
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- SM
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1–5 of 1.1K
Institutions
562
University of Toronto
Toronto, Canada
9 h-index
15 publications
842 citations
University of California San Diego
San Diego, United States
8 h-index
14 publications
1.4K citations
Columbia University
New York, United States
7 h-index
11 publications
567 citations
Cornell University
Ithaca, United States
7 h-index
11 publications
863 citations
Istanbul Technical University
Istanbul, Türkiye
6 h-index
12 publications
824 citations
Centre National de la Recherche Scientifique
Paris, France
6 h-index
11 publications
575 citations
University of Illinois Urbana-Champaign
Urbana, United States
6 h-index
9 publications
525 citations
Harvard University
Cambridge, United States
5 h-index
16 publications
1.5K citations
1–8 of 562
Venues
- IEEE Transactions on Information Theory
15 publications · 1.3K citations
13
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- IEEE Transactions on Communications
10 publications · 708 citations
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- Journal of the American Statistical Association
9 publications · 506 citations
9
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- IEEE Signal Processing Letters
9 publications · 1.4K citations
9
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- PLoS ONE
7 publications · 420 citations
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