Scalable Bayesian Learning for State Space Models using Variational Inference with SMC Samplers.
Marcel HirtPetros DellaportasPublished in: AISTATS (2019)
Keyphrases
- bayesian learning
- variational inference
- posterior distribution
- state space
- bayesian inference
- model selection
- markov chain monte carlo
- probabilistic model
- parameter estimation
- bayesian framework
- probability distribution
- gaussian process
- reinforcement learning
- statistical methods
- particle filter
- markov chain
- cross validation
- posterior probability
- graphical models
- active learning
- feature space
- support vector