An introduction to hidden Markov models. by Schuster-Böckler, B, Bateman, A

“…This unit introduces the concept of hidden Markov models in computational biology. It describes them using simple biological examples, requiring as little mathematical knowledge as possible. …”

Complexity of comparing hidden markov models by Lyngsø, R, Pedersen, C

“…The basic theory of hidden Markov models was developed and applied to problems in speech recognition in the late 1960's, and has since then been applied to numerous problems, e.g. biological sequence analysis. …”

Infinite hierarchical hidden Markov models by Heller, K, Teh, Y, Görür, D

“…In this paper we present the Infinite Hierarchical Hidden Markov Model (IHHMM), a nonparametric generalization of Hierarchical Hidden Markov Models (HHMMs). …”

The infinite factorial hidden Markov model by Van Gael, J, Teh, Y, Ghahramani, Z

“…We use this stochastic process to build a nonparametric extension of the factorial hidden Markov model. After constructing an inference scheme which combines slice sampling and dynamic programming we demonstrate how the infinite factorial hidden Markov model can be used for blind source separation.…”

Ensemble hidden Markov models for biosignal analysis by Rezek, I, Roberts, S

Equivalence of hidden Markov models with continuous observations by Darwin, O, Kiefer, SM

“…We consider Hidden Markov Models that emit sequences of observations that are drawn from continuous distributions. …”

Beam sampling for the infinite hidden Markov model by Van Gael, J, Saatci, Y, Teh, Y, Ghahramani, Z

“…The infinite hidden Markov model is a non-parametric extension of the widely used hidden Markov model. …”

HMMoC--a compiler for hidden Markov models. by Lunter, G

“…UNLABELLED: Hidden Markov models are widely applied within computational biology. …”

Coupled hidden Markov models for biosignal interaction modelling by Rezek, I, Sykacek, P, Roberts, S, IEE, IEE

Side Channel Attack By Using Hidden Markov Model by Nguyen, L

Learning interaction dynamics with coupled hidden Markov models by Rezek, I, Sykacek, P, Roberts, S

“…Interactions between such signals can be modelled in state space rather than observation space, i.e. interactions are modelled after first translating the observations into a common domain. Coupled hidden Markov models (CHMM) are such state-space models. …”

Collapsed Variational Bayesian Inference for Hidden Markov Models by Wang, P, Blunsom, P

On computing the total variation distance of hidden Markov models by Kiefer, S

“…We prove results on the decidability and complexity of computing the total variation distance (equivalently, the L1-distance) of hidden Markov models (equivalently, labelled Markov chains). …”

Stochastic collapsed variational inference for hidden Markov models by Wang, P, Blunsom, P

“…In this paper, we propose a stochastic collapsed variational inference algorithm for hidden Markov models, in a sequential data setting. Given a collapsed hidden Markov Model, we break its long Markov chain into a set of short subchains. …”

Uncertainty and filtering of hidden Markov models in discrete time by Cohen, SN

Collapsed Variational Bayesian Inference for Hidden Markov Models by Wang, P, Blunsom, P

On the sequential probability ratio test in hidden Markov models by Darwin, O, Kiefer, S

“…<p>We consider the Sequential Probability Ratio Test applied to Hidden Markov Models. Given two Hidden Markov Models and a sequence of observations generated by one of them, the Sequential Probability Ratio Test attempts to decide which model produced the sequence. …”

On-line inference for hidden Markov models via particle filters by Fearnhead, P, Clifford, P

“…We consider the on-line Bayesian analysis of data by using a hidden Markov model, where inference is tractable conditional on the history of the state of the hidden component. …”

Analyticity of entropy rates of continuous-state hidden Markov models by Tadic, V, Doucet, A

“…The analyticity of the entropy and relative entropy rates of continuous-state hidden Markov models is studied here. Using the analytic continuation principle and the stability properties of the optimal filter, the analyticity of these rates is established for analytically parameterized models. …”

Maximum a Posteriori Estimation of Coupled Hidden Markov Models. by Rezek, I, Gibbs, M, Roberts, S

“…Coupled Hidden Markov Models (CHMM) are a tool which model interactions between variables in state space rather than observation space. …”