Higher-order Markov Models
Higher-Order Markov Models is a type of stochastic process model in which the probability distribution of future states depends on a fixed number of preceding states greater than one, thereby extending the first-order Markov property by incorporating longer memory dependencies in state transitions.
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8.8K
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343
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224
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2017–2026
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University of Hong Kong
Pok Fu Lam, Hong Kong
6 h-index
10 publications
326 citations

University of Waterloo
Waterloo, Canada
4 h-index
7 publications
457 citations
Nanyang Technological University
Singapore, Singapore
3 h-index
5 publications
558 citations
Kuwait University
Kuwait City, Kuwait
3 h-index
5 publications
233 citations
ETH Zurich
Zurich, Switzerland
3 h-index
6 publications
440 citations

University of Passau
Passau, Germany
3 h-index
6 publications
440 citations
University of Chicago
Chicago, United States
3 h-index
3 publications
155 citations

Stellenbosch University
Stellenbosch, South Africa
3 h-index
4 publications
80 citations
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5 publications · 498 citations
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4 publications · 193 citations
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3 publications · 87 citations
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3 publications · 181 citations
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3 publications · 199 citations
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