Search Results for author:
Found 5 papers, 2 papers with code
Variational State and Parameter Estimation
In this work, a variational approach is used to provide an assumed density which approximates the desired, intractable, distribution.
Variational System Identification for Nonlinear State-Space Models
This paper considers parameter estimation for nonlinear state-space models, which is an important but challenging problem.
Correlated pseudo-marginal Metropolis-Hastings using quasi-Newton proposals
Pseudo-marginal Metropolis-Hastings (pmMH) is a versatile algorithm for sampling from target distributions which are not easy to evaluate point-wise.
Constructing Metropolis-Hastings proposals using damped BFGS updates
The computation of Bayesian estimates of system parameters and functions of them on the basis of observed system performance data is a common problem within system identification.
Computation Computational Finance
A Bayesian Filtering Algorithm for Gaussian Mixture Models
A Bayesian filtering algorithm is developed for a class of state-space systems that can be modelled via Gaussian mixtures.
