Scalable Bayesian Learning for State Space Models using Variational Inference with SMC Samplers

Marcel Hirt, Petros Dellaportas

We present a scalable approach to performing approximate fully Bayesian inference in generic state space models. The proposed method is an alternative to particle MCMC that provide…