scholarly journals An observed sequence probability estimate in binary linear hidden Markov models with posterior inference in algebraic Bayesian networks

2014 ◽  
Vol 2 (13) ◽  
pp. 122
Author(s):  
Maria Petrovna Momzikova ◽  
Olga Igorevna Velikodnaya ◽  
Mikhail Iakovlevich Pinsky ◽  
Alexander Vladimirovich Sirotkin ◽  
Alexander Lvovich Tulupyev ◽  
...  
2014 ◽  
Vol 1 (24) ◽  
pp. 165
Author(s):  
Alexander Lvovich Tulupyev ◽  
Andrey Alexandrovich Filchenkov ◽  
Anton Mikhailovich Alexeyev

Author(s):  
ZOUBIN GHAHRAMANI

We provide a tutorial on learning and inference in hidden Markov models in the context of the recent literature on Bayesian networks. This perspective makes it possible to consider novel generalizations of hidden Markov models with multiple hidden state variables, multiscale representations, and mixed discrete and continuous variables. Although exact inference in these generalizations is usually intractable, one can use approximate inference algorithms such as Markov chain sampling and variational methods. We describe how such methods are applied to these generalized hidden Markov models. We conclude this review with a discussion of Bayesian methods for model selection in generalized HMMs.


2014 ◽  
Vol 1 (20) ◽  
pp. 186
Author(s):  
Leonid Markovich Revzin ◽  
Andrey Alexandrovich Filchenkov ◽  
Alexander Lvovich Tulupyev

2014 ◽  
Vol 1 (12) ◽  
pp. 134
Author(s):  
Maria Petrovna Momzikova ◽  
Olga Igorevna Velikodnaya ◽  
Mikhail Iakovlevich Pinsky ◽  
Alexander Vladimirovich Sirotkin ◽  
Alexander Lvovich Tulupyev ◽  
...  

Author(s):  
Krishna Pattipati ◽  
Peter Willett ◽  
Jeffrey Allanach ◽  
Haiying Tu ◽  
Satnam Singh

2019 ◽  
Vol 2019 (15) ◽  
pp. 41-1-41-7
Author(s):  
Kurt Pichler ◽  
Sandra Haindl ◽  
Daniel Reischl ◽  
Martin Trinkl

Sign in / Sign up

Export Citation Format

Share Document