47 citations · 294 across the 31 of their papers we have counts for
10 papers · 1 filter
Evaluating the squared-exponential covariance function in Gaussian processes with integral observations
J. N. Hendriks, C. Jidling, A. Wills +1
This paper deals with the evaluation of double line integrals of the squared exponential covariance function. We propose a new approach in which the double integral is reduced to a…
A fast quasi-Newton-type method for large-scale stochastic optimisation
Adrian Wills, Carl Jidling, Thomas Schon
During recent years there has been an increased interest in stochastic adaptations of limited memory quasi-Newton methods, which compared to pure gradient-based routines can improv…
Tomographic Reconstruction of Two-Dimensional Residual Strain Fields from Bragg-Edge Neutron Imaging
Alexander Gregg, Johannes Hendriks, Christopher Wensrich +7
Bragg-edge strain imaging from energy-resolved neutron transmission measurements poses an interesting tomography problem. The solution to this problem will allow the reconstruction…
Robust Inference of Two-Dimensional Strain Fields from Diffraction-based Measurements
J. N. Hendriks, C. M. Wensrich, A. Wills +2
Diffraction-based methods have become an invaluable tool for the detailed assessment of residual strain and stress within experimental mechanics. These methods typically measure a…
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…
Implementation of Traction Constraints in Bragg-edge Neutron Transmission Strain Tomography
J. N. Hendriks, A. W. T. Gregg, C. M. Wensrich +1
Several recent methods for tomographic reconstruction of stress and strain fields from Bragg-edge neutron strain images have been proposed in the literature. This paper presents an…
Stochastic quasi-Newton with adaptive step lengths for large-scale problems
Adrian Wills, Thomas Schön
We provide a numerically robust and fast method capable of exploiting the local geometry when solving large-scale stochastic optimisation problems. Our key innovation is an auxilia…
Probabilistic modelling and reconstruction of strain
Carl Jidling, Johannes Hendriks, Niklas Wahlström +4
This paper deals with modelling and reconstruction of strain fields, relying upon data generated from neutron Bragg-edge measurements. We propose a probabilistic approach in which…
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.…
Sparse Bayesian ARX models with flexible noise distributions
Johan Dahlin, Adrian Wills, Brett Ninness
This paper considers the problem of estimating linear dynamic system models when the observations are corrupted by random disturbances with nonstandard distributions. The paper is…