Latent Markov models in the estimation of distribution and association maps for species
Tekijät
Päivämäärä
2001Pääsyrajoitukset
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Statistical analysis of life sequence data
Helske, Satu (University of Jyväskylä, 2016) -
Conditional particle filters with diffuse initial distributions
Karppinen, Santeri; Vihola, Matti (Springer, 2021)Conditional particle filters (CPFs) are powerful smoothing algorithms for general nonlinear/non-Gaussian hidden Markov models. However, CPFs can be inefficient or difficult to apply with diffuse initial distributions, which ... -
Optimization of Linearized Belief Propagation for Distributed Detection
Abdi, Younes; Ristaniemi, Tapani (IEEE, 2020)In this paper, we investigate distributed inference schemes, over binary-valued Markov random fields, which are realized by the belief propagation (BP) algorithm. We first show that a decision variable obtained by the BP ... -
The Max-Product Algorithm Viewed as Linear Data-Fusion : A Distributed Detection Scenario
Abdi, Younes; Ristaniemi, Tapani (Institute of Electrical and Electronics Engineers (IEEE), 2020)In this paper, we disclose the statistical behavior of the max-product algorithm configured to solve a maximum a posteriori (MAP) estimation problem in a network of distributed agents. Specifically, we first build a ... -
Associations between observed patterns of classroom interactions and teacher wellbeing in lower secondary school
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