Results 11 to 20 of about 511,753 (356)
Scoring hidden Markov models [PDF]
Bioinformatics, 1997 Statistical sequence comparison techniques, such as hidden Markov models and generalized profiles, calculate the probability that a sequence was generated by a given model. Log-odds scoring is a means of evaluating this probability by comparing it to a null hypothesis, usually a simpler statistical model intended to represent the universe of sequences ...
C, Barrett, R, Hughey, K, Karplus
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Factorial Hidden Markov Models [PDF]
Machine Learning, 1997 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ghahramani, Zoubin, Jordan, Michael I.
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Visual tracking using interactive factorial hidden Markov models
IET Signal Processing, 2021 The authors present a novel tracking algorithm based on a factorial hidden Markov model (FHMM) that can utilise the structured information of a target.
Jin Wook Paeng, Junseok Kwon
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Utile distinction hidden Markov models [PDF]
Twenty-first international conference on Machine learning - ICML '04, 2004 This paper addresses the problem of constructing good action selection policies for agents acting in partially observable environments, a class of problems generally known as Partially Observable Markov Decision Processes. We present a novel approach that uses a modification of the well-known Baum-Welch algorithm for learning a Hidden Markov Model (HMM)
Wierstra, D., Wiering, M.A.
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ToPS: a framework to manipulate probabilistic models of sequence data. [PDF]
PLoS Computational Biology, 2013 Discrete Markovian models can be used to characterize patterns in sequences of values and have many applications in biological sequence analysis, including gene prediction, CpG island detection, alignment, and protein profiling.
André Yoshiaki Kashiwabara +5 more
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Frontiers in Ecology and Evolution, 2021 The study of animal behavioral states inferred through hidden Markov models and similar state switching models has seen a significant increase in popularity in recent years.
Giada Sacchi, Ben Swallow
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Flexible and practical modeling of animal telemetry data: hidden Markov models and extensions [PDF]
, 2012 We discuss hidden Markov-type models for fitting a variety of multistate random walks to wildlife movement data. Discrete-time hidden Markov models (HMMs) achieve considerable computational gains by focusing on observations that are regularly spaced in ...
Langrock, R. +5 more
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Generalized Hidden Markov Models for Phylogenetic Comparative Datasets
bioRxiv, 2020 Hidden Markov models (HMM) have emerged as an important tool for understanding the evolution of characters that take on discrete states. Their flexibility and biological sensibility make them appealing for many phylogenetic comparative applications ...
James D. Boyko, Jeremy M Beaulieu
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Journal of Artificial Intelligence Research, 2006 Logical hidden Markov models (LOHMMs) upgrade traditional hidden Markov models to deal with sequences of structured symbols in the form of logical atoms, rather than flat characters. This note formally introduces LOHMMs and presents solutions to the three central inference problems for LOHMMs: evaluation, most likely hidden state sequence and ...
Kersting, K., De Raedt, Luc, Raiko, T.
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SOLUTION TO EVALUATION PROBLEM OF HIDDEN SEMI-MARKOV QP-MODELS
Advanced Engineering Research, 2014 A hidden semi-Markov QP-model is considered; and the way it could be embedded in a general hidden semi-Markov model is shown. The estimation problem (the first of three classical theory problems of the hidden Markov models and hidden semi-Markov models ...
V. M. Deundyak, M. A. Zhdanova
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