92 citations · 498 across the 46 of their papers we have counts for
8 papers · 1 filter
Weak convergence of Galerkin approximations for fractional elliptic stochastic PDEs with spatial white noise
David Bolin, Kristin Kirchner, Mihály Kovács
The numerical approximation of the solution to a stochastic partial differential equation with additive spatial white noise on a bounded domain is considered. The differential oper…
The rational SPDE approach for Gaussian random fields with general smoothness
David Bolin, Kristin Kirchner
A popular approach for modeling and inference in spatial statistics is to represent Gaussian random fields as solutions to stochastic partial differential equations (SPDEs) of the…
Level set Cox processes
Anders Hildeman, David Bolin, Jonas Wallin +1
The log-Gaussian Cox process (LGCP) is a popular point process for modeling non-interacting spatial point patterns. This paper extends the LGCP model to handle data exhibiting fund…
A Bayesian General Linear Modeling Approach to Cortical Surface fMRI Data Analysis
Amanda Mejia, Yu Ryan Yue, David Bolin +2
Cortical surface fMRI (cs-fMRI) has recently grown in popularity versus traditional volumetric fMRI, as it allows for more meaningful spatial smoothing and is more compatible with…
Comparison of hidden Markov chain models and hidden Markov random field models in estimation of computed tomography images
Kristi Kuljus, Fekadu L. Bayisa, David Bolin +2
There is an interest to replace computed tomography (CT) images with magnetic resonance (MR) images for a number of diagnostic and therapeutic workflows. In this article, predictin…
Efficient Covariance Approximations for Large Sparse Precision Matrices
Per Sidén, Finn Lindgren, David Bolin +1
The use of sparse precision (inverse covariance) matrices has become popular because they allow for efficient algorithms for joint inference in high-dimensional models. Many applic…