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stat.ME2023
State and parameter learning with PaRIS particle Gibbs
Gabriel Cardoso, Yazid Janati El Idrissi, Sylvain Le Corff +2
Non-linear state-space models, also known as general hidden Markov models, are ubiquitous in statistical machine learning, being the most classical generative models for serial dat…
stat.ME2022
Particle-based, rapid incremental smoother meets particle Gibbs
Gabriel Cardoso, Eric Moulines, Jimmy Olsson
The particle-based, rapid incremental smoother (PARIS) is a sequential Monte Carlo technique allowing for efficient online approximation of expectations of additive functionals und…