Mattias Villani

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Linköping University

Bayesian Optimization of Hyperparameters when the Marginal Likelihood is Estimated by MCMC

Bayesian models often involve a small set of hyperparameters determined ...
04/21/2020 ∙ by Oskar Gustafsson, et al. ∙ 0 ∙ share

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When are Bayesian model probabilities overconfident?

Bayesian model comparison is often based on the posterior distribution o...
03/09/2020 ∙ by Oscar Oelrich, et al. ∙ 0 ∙ share

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A Bayesian Dynamic Multilayered Block Network Model

As network data become increasingly available, new opportunities arise t...
11/29/2019 ∙ by Hector Rodriguez-Deniz, et al. ∙ 0 ∙ share

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Spectral Subsampling MCMC for Stationary Time Series

Bayesian inference using Markov Chain Monte Carlo (MCMC) on large datase...
10/30/2019 ∙ by Robert Salomone, et al. ∙ 0 ∙ share

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Anatomically informed Bayesian spatial priors for fMRI analysis

Existing Bayesian spatial priors for functional magnetic resonance imagi...
10/18/2019 ∙ by David Abramian, et al. ∙ 0 ∙ share

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Spatial 3D Matérn priors for fast whole-brain fMRI analysis

Bayesian whole-brain functional magnetic resonance imaging (fMRI) analys...
06/25/2019 ∙ by Per Sidén, et al. ∙ 0 ∙ share

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Real-Time Robotic Search using Hierarchical Spatial Point Processes

Aerial robots hold great potential for aiding Search and Rescue (SAR) ef...
03/25/2019 ∙ by Olov Andersson, et al. ∙ 0 ∙ share

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Modeling Text Complexity using a Multi-Scale Probit

We present a novel model for text complexity analysis which can be fitte...
11/12/2018 ∙ by Johan Falkenjack, et al. ∙ 0 ∙ share

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Subsampling MCMC - An introduction for the survey statistician

The rapid development of computing power and efficient Markov Chain Mont...
07/23/2018 ∙ by Matias Quiroz, et al. ∙ 0 ∙ share

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Subsampling MCMC - A review for the survey statistician

The rapid development of computing power and efficient Markov Chain Mont...
07/23/2018 ∙ by Matias Quiroz, et al. ∙ 0 ∙ share

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Bayesian Sequential Inference in Dynamic Survival Models

Dynamic hazard models are applied to analyze time-varying effects of cov...
06/19/2018 ∙ by Parfait Munezero, et al. ∙ 0 ∙ share

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Hamiltonian Monte Carlo with Energy Conserving Subsampling

Hamiltonian Monte Carlo (HMC) has recently received considerable attenti...
08/02/2017 ∙ by Khue-Dung Dang, et al. ∙ 0 ∙ share

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Tree Ensembles with Rule Structured Horseshoe Regularization

We propose a new Bayesian model for flexible nonlinear regression and cl...
02/16/2017 ∙ by Malte Nalenz, et al. ∙ 0 ∙ share

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Exact Subsampling MCMC

Speeding up Markov Chain Monte Carlo (MCMC) for data sets with many obse...
03/27/2016 ∙ by Matias Quiroz, et al. ∙ 0 ∙ share

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DOLDA - a regularized supervised topic model for high-dimensional multi-class regression

Generating user interpretable multi-class predictions in data rich envir...
01/31/2016 ∙ by Måns Magnusson, et al. ∙ 0 ∙ share

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Bayesian optimisation for fast approximate inference in state-space models with intractable likelihoods

We consider the problem of approximate Bayesian parameter inference in n...
06/23/2015 ∙ by Johan Dahlin, et al. ∙ 0 ∙ share

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Sparse Partially Collapsed MCMC for Parallel Inference in Topic Models

Topic models, and more specifically the class of Latent Dirichlet Alloca...
06/11/2015 ∙ by Måns Magnusson, et al. ∙ 0 ∙ share

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Speeding Up MCMC by Efficient Data Subsampling

We propose Subsampling MCMC, a Markov Chain Monte Carlo (MCMC) framework...
04/16/2014 ∙ by Matias Quiroz, et al. ∙ 0 ∙ share

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Mattias Villani

Featured Co-authors

Thomas B. Schön

Aki Vehtari

Minh-Ngoc Tran

Robert Kohn

Anders Eklund

Johan Dahlin

David Bolin

Måns Magnusson

Matias Quiroz

David Broman

Hans Knutsson

Bayesian Optimization of Hyperparameters when the Marginal Likelihood is Estimated by MCMC

When are Bayesian model probabilities overconfident?

A Bayesian Dynamic Multilayered Block Network Model

Spectral Subsampling MCMC for Stationary Time Series

Anatomically informed Bayesian spatial priors for fMRI analysis

Spatial 3D Matérn priors for fast whole-brain fMRI analysis

Real-Time Robotic Search using Hierarchical Spatial Point Processes

Modeling Text Complexity using a Multi-Scale Probit

Subsampling MCMC - An introduction for the survey statistician

Subsampling MCMC - A review for the survey statistician

Bayesian Sequential Inference in Dynamic Survival Models

Hamiltonian Monte Carlo with Energy Conserving Subsampling

Tree Ensembles with Rule Structured Horseshoe Regularization

Exact Subsampling MCMC

DOLDA - a regularized supervised topic model for high-dimensional multi-class regression

Bayesian optimisation for fast approximate inference in state-space models with intractable likelihoods

Sparse Partially Collapsed MCMC for Parallel Inference in Topic Models

Speeding Up MCMC by Efficient Data Subsampling