26 citations · 42 across the 4 of their papers we have counts for
5 papers
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…
Reliable Semi-Supervised Learning when Labels are Missing at Random
Xiuming Liu, Dave Zachariah, Johan Wågberg +1
Semi-supervised learning methods are motivated by the availability of large datasets with unlabeled features in addition to labeled data. Unlabeled data is, however, not guaranteed…
Regularized parametric system identification: a decision-theoretic formulation
Johan Wågberg, Dave Zachariah, Thomas B. Schön
Parametric prediction error methods constitute a classical approach to the identification of linear dynamic systems with excellent large-sample properties. A more recent regularize…
Prediction performance after learning in Gaussian process regression
Johan Wågberg, Dave Zachariah, Thomas B. Schön +1
This paper considers the quantification of the prediction performance in Gaussian process regression. The standard approach is to base the prediction error bars on the theoretical…
Linear System Identification via EM with Latent Disturbances and Lagrangian Relaxation
Jack Umenberger, Johan Wågberg, Ian R. Manchester +1
In the application of the Expectation Maximization algorithm to identification of dynamical systems, internal states are typically chosen as latent variables, for simplicity. In th…