Merging MCMC Subposteriors through Gaussian-Process Approximations
Bayesian Analysis
Particle approximations of the score and observed information matrix for parameter estimation in state–space models with linear computational cost
Journal of Computational and Graphical Statistics
Particle Metropolis-adjusted Langevin algorithms
Biometrika
Parameter estimation for state space models using sequential Monte Carlo algorithms
PhD Thesis
Sequential Monte Carlo methods for state and parameter estimation in abruptly changing environments
IEEE Transactions on Signal Processing
Bearings-only tracking with particle filtering for joint parameter learning and state estimation
15th International Conference on Information Fusion
Particle learning methods for state and parameter estimation
9th IET Data Fusion and Target Tracking Conference