196 citations · 699 across the 80 of their papers we have counts for
4 papers · 1 filter
Nonlinear State Space Model Identification Using a Regularized Basis Function Expansion
Andreas Svensson, Thomas B. Schön, Arno Solin +1
This paper is concerned with black-box identification of nonlinear state space models. By using a basis function expansion within the state space model, we obtain a flexible struct…
Modeling and interpolation of the ambient magnetic field by Gaussian processes
Arno Solin, Manon Kok, Niklas Wahlström +2
Anomalies in the ambient magnetic field can be used as features in indoor positioning and navigation. By using Maxwell's equations, we derive and present a Bayesian non-parametric…
Computationally Efficient Bayesian Learning of Gaussian Process State Space Models
Andreas Svensson, Arno Solin, Simo Särkkä +1
Gaussian processes allow for flexible specification of prior assumptions of unknown dynamics in state space models. We present a procedure for efficient Bayesian learning in Gaussi…
Rao-Blackwellized particle smoothers for conditionally linear Gaussian models
Fredrik Lindsten, Pete Bunch, Simo Särkkä +2
Sequential Monte Carlo (SMC) methods, such as the particle filter, are by now one of the standard computational techniques for addressing the filtering problem in general state-spa…