47 citations · 294 across the 31 of their papers we have counts for
4 papers · 1 filter
Nonlinear System Identification: Learning while respecting physical models using a sequential Monte Carlo method
Anna Wigren, Johan Wågberg, Fredrik Lindsten +2
Identification of nonlinear systems is a challenging problem. Physical knowledge of the system can be used in the identification process to significantly improve the predictive per…
Correlated pseudo-marginal Metropolis-Hastings using quasi-Newton proposals
Johan Dahlin, Adrian Wills, Brett Ninness
Pseudo-marginal Metropolis-Hastings (pmMH) is a versatile algorithm for sampling from target distributions which are not easy to evaluate point-wise. However, pmMH requires good pr…
Constructing Metropolis-Hastings proposals using damped BFGS updates
Johan Dahlin, Adrian Wills, Brett Ninness
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.…
Newton-based maximum likelihood estimation in nonlinear state space models
Manon Kok, Johan Dahlin, Thomas B. Schön +1
Maximum likelihood (ML) estimation using Newton's method in nonlinear state space models (SSMs) is a challenging problem due to the analytical intractability of the log-likelihood…