156 citations · 361 across the 32 of their papers we have counts for
5 papers · 1 filter
Bayesian Non-Central Chi Regression For Neuroimaging
Bertil Wegmann, Anders Eklund, Mattias Villani
We propose a regression model for non-central (NC-) distributed functional magnetic resonance imaging (fMRI) and diffusion weighted imaging (DWI) data, with the heteroscedas…
A Bayesian Heteroscedastic GLM with Application to fMRI Data with Motion Spikes
Anders Eklund, Martin A. Lindquist, Mattias Villani
We propose a voxel-wise general linear model with autoregressive noise and heteroscedastic noise innovations (GLMH) for analyzing functional magnetic resonance imaging (fMRI) data.…
Fast Bayesian whole-brain fMRI analysis with spatial 3D priors
Per Sidén, Anders Eklund, David Bolin +1
Spatial whole-brain Bayesian modeling of task-related functional magnetic resonance imaging (fMRI) is a great computational challenge. Most of the currently proposed methods theref…
The block-Poisson estimator for optimally tuned exact subsampling MCMC
Matias Quiroz, Minh-Ngoc Tran, Mattias Villani +2
Speeding up Markov Chain Monte Carlo (MCMC) for datasets with many observations by data subsampling has recently received considerable attention. A pseudo-marginal MCMC method is p…
DOLDA - a regularized supervised topic model for high-dimensional multi-class regression
Måns Magnusson, Leif Jonsson, Mattias Villani
Generating user interpretable multi-class predictions in data rich environments with many classes and explanatory covariates is a daunting task. We introduce Diagonal Orthant Laten…