18 citations · 27 across the 4 of their papers we have counts for
4 papers
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…
Modelling multi-scale state-switching functional data with hidden Markov models
Evan Sidrow, Nancy Heckman, Sarah M. E. Fortune +3
Data sets comprised of sequences of curves sampled at high frequencies in time are increasingly common in practice, but they can exhibit complicated dependence structures that cann…
Bayesian Melding of the Dead-Reckoned Path and GPS Measurements for an Accurate and High-Resolution Path of Marine Mammals
Yang Liu, Brian C. Battaile, James V. Zidek +1
With the recent advances in electrical engineering, devices attached to free-ranging marine mammals today can collect oceanographic data in remarkable high spatial-temporal resolut…