196 citations · 699 across the 80 of their papers we have counts for
9 papers · 1 filter
Non-linear Gaussian smoothing with Taylor moment expansion
Zheng Zhao, Simo Särkkä
This letter is concerned with solving continuous-discrete Gaussian smoothing problems by using the Taylor moment expansion (TME) scheme. In the proposed smoothing method, we apply…
A Survey of Monte Carlo Methods for Parameter Estimation
D. Luengo, L. Martino, M. Bugallo +2
Statistical signal processing applications usually require the estimation of some parameters of interest given a set of observed data. These estimates are typically obtained either…
Kalman filtering with empirical noise models
Matti Raitoharju, Henri Nurminen, Demet Cilden-Guler +1
Most Kalman filter extensions assume Gaussian noise and when the noise is non-Gaussian, usually other types of filters are used. These filters, such as particle filter variants, ar…
System identification using Bayesian neural networks with nonparametric noise models
Christos Merkatas, Simo Särkkä
System identification is of special interest in science and engineering. This article is concerned with a system identification problem arising in stochastic dynamic systems, where…
Temporal Parallelisation of Dynamic Programming and Linear Quadratic Control
Simo Särkkä, Ángel F. García-Fernández
This paper proposes a general formulation for temporal parallelisation of dynamic programming for optimal control problems. We derive the elements and associative operators to be a…
Temporal Gaussian Process Regression in Logarithmic Time
Adrien Corenflos, Zheng Zhao, Simo Särkkä
The aim of this article is to present a novel parallelization method for temporal Gaussian process (GP) regression problems. The method allows for solving GP regression problems in…