1 citations · 3 across the 3 of their papers we have counts for
3 papers
Mixing time of the conditional backward sampling particle filter
Joona Karjalainen, Anthony Lee, Sumeetpal S. Singh +1
The conditional backward sampling particle filter (CBPF) is a powerful Markov chain Monte Carlo sampler for general state space hidden Markov model (HMM) smoothing. It was proposed…
On the Forgetting of Particle Filters
Joona Karjalainen, Anthony Lee, Sumeetpal S. Singh +1
We study the forgetting properties of the particle filter when its state - the collection of particles - is regarded as a Markov chain. Under a strong mixing assumption on the part…
Monte Carlo twisting for particle filters
Joshua J Bon, Christopher Drovandi, Anthony Lee
We consider the problem of designing efficient particle filters for twisted Feynman--Kac models. Particle filters using twisted models can deliver low error approximations of stati…