2 citations · 3 across the 3 of their papers we have counts for
3 papers
Flexible unimodal density estimation in hidden Markov models
Jan-Ole Koslik, Fanny Dupont, Marie Auger-Méthé +3
1. Hidden Markov models (HMMs) are powerful tools for modelling time-series data with underlying state structure. However, selecting appropriate parametric forms for the state-depe…
Incorporating sparse labels into hidden Markov models using weighted likelihoods improves accuracy and interpretability in biologging studies
Evan Sidrow, Nancy Heckman, Tess M. McRae +4
Ecologists often use a hidden Markov model to decode a latent process, such as a sequence of an animal's behaviours, from an observed biologging time series. Modern technological d…
Variance-Reduced Stochastic Optimization for Efficient Inference of Hidden Markov Models
Evan Sidrow, Nancy Heckman, Alexandre Bouchard-Côté +3
Hidden Markov models (HMMs) are popular models to identify a finite number of latent states from sequential data. However, fitting them to large data sets can be computationally de…