4 citations · 11 across the 9 of their papers we have counts for
6 papers · 1 filter
Variational State and Parameter Estimation
Jarrad Courts, Johannes Hendriks, Adrian Wills +2
This paper considers the problem of computing Bayesian estimates of both states and model parameters for nonlinear state-space models. Generally, this problem does not have a tract…
Variational System Identification for Nonlinear State-Space Models
Jarrad Courts, Adrian Wills, Thomas Schön +1
This paper considers parameter estimation for nonlinear state-space models, which is an important but challenging problem. We address this challenge by employing a variational infe…
Practical Bayesian System Identification using Hamiltonian Monte Carlo
Johannes Hendriks, Adrian Wills, Brett Ninness +1
This paper considers Bayesian parameter estimation of dynamic systems using a Markov Chain Monte Carlo (MCMC) approach. The Metroplis-Hastings (MH) algorithm is employed, and the m…
A Variational Expectation-Maximisation Algorithm for Learning Jump Markov Linear Systems
Mark P. Balenzuela, Adrian G. Wills, Christopher Renton +1
Jump Markov linear systems (JMLS) are a useful class which can be used to model processes which exhibit random changes in behavior during operation. This paper presents a numerical…
A New Smoothing Algorithm for Jump Markov Linear Systems
Mark P. Balenzuela, Adrian G. Wills, Christopher Renton +1
This paper presents a method for calculating the smoothed state distribution for Jump Markov Linear Systems. More specifically, the paper details a novel two-filter smoother that p…
Bayesian Parameter Identification for Jump Markov Linear Systems
Mark P. Balenzuela, Adrian G. Wills, Christopher Renton +1
This paper presents a Bayesian method for identification of jump Markov linear system parameters. A primary motivation is to provide accurate quantification of parameter uncertaint…