Up-to-date results on the application of Markov models to chromosome analysis are presented. On the one hand, this means using continuous Hidden Markov Models (HMMs) instead of dis...
The context-independent deep belief network (DBN) hidden Markov model (HMM) hybrid architecture has recently achieved promising results for phone recognition. In this work, we pro...
We show that it is possible to extend hidden Markov models to have a countably infinite number of hidden states. By using the theory of Dirichlet processes we can implicitly integ...
Matthew J. Beal, Zoubin Ghahramani, Carl Edward Ra...
Standard hidden Markov models (HMM's) have been studied extensively in the last two decades. It is well known that these models assume state conditional independence of the ob...
Dimensionality reduction, spectral classification and segmentation are the three main problems in hyperspectral image analysis. In this paper we propose a Bayesian estimation appr...
Nadia Bali, Ali Mohammad-Djafari, Adel Mohammadpou...