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01/19/2022
Bayesian Prediction with Covariates Subject to Detection Limits
Missing values in covariates due to censoring by signal interference or ...
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12/14/2021
Local Prediction Pools
We propose local prediction pools as a method for combining the predicti...
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12/08/2021
Bayesian Modeling of Effective and Functional Brain Connectivity using Hierarchical Vector Autoregressions
Analysis of brain connectivity is important for understanding how inform...
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09/23/2021
Dynamic Mixture of Experts Models for Online Prediction
A mixture of experts models the conditional density of a response variab...
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06/25/2021
Robust Real-Time Delay Predictions in a Network of High-Frequency Urban Buses
Providing transport users and operators with accurate forecasts on trave...
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04/05/2021
Spectral Subsampling MCMC for Stationary Multivariate Time Series
Spectral subsampling MCMC was recently proposed to speed up Markov chain...
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04/21/2020
Bayesian Optimization of Hyperparameters when the Marginal Likelihood is Estimated by MCMC
Bayesian models often involve a small set of hyperparameters determined ...
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03/09/2020
When are Bayesian model probabilities overconfident?
Bayesian model comparison is often based on the posterior distribution o...
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11/29/2019
A Bayesian Dynamic Multilayered Block Network Model
As network data become increasingly available, new opportunities arise t...
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10/30/2019
Spectral Subsampling MCMC for Stationary Time Series
Bayesian inference using Markov Chain Monte Carlo (MCMC) on large datase...
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10/18/2019
Anatomically informed Bayesian spatial priors for fMRI analysis
Existing Bayesian spatial priors for functional magnetic resonance imagi...
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06/25/2019
Spatial 3D Matérn priors for fast whole-brain fMRI analysis
Bayesian whole-brain functional magnetic resonance imaging (fMRI) analys...
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03/25/2019
Real-Time Robotic Search using Hierarchical Spatial Point Processes
Aerial robots hold great potential for aiding Search and Rescue (SAR) ef...
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11/12/2018
Modeling Text Complexity using a Multi-Scale Probit
We present a novel model for text complexity analysis which can be fitte...
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07/23/2018
Subsampling MCMC - An introduction for the survey statistician
The rapid development of computing power and efficient Markov Chain Mont...
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07/23/2018
Subsampling MCMC - A review for the survey statistician
The rapid development of computing power and efficient Markov Chain Mont...
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06/19/2018
Bayesian Sequential Inference in Dynamic Survival Models
Dynamic hazard models are applied to analyze time-varying effects of cov...
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08/02/2017
Hamiltonian Monte Carlo with Energy Conserving Subsampling
Hamiltonian Monte Carlo (HMC) has recently received considerable attenti...
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02/16/2017
Tree Ensembles with Rule Structured Horseshoe Regularization
We propose a new Bayesian model for flexible nonlinear regression and cl...
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03/27/2016
Exact Subsampling MCMC
Speeding up Markov Chain Monte Carlo (MCMC) for data sets with many obse...
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01/31/2016
DOLDA - a regularized supervised topic model for high-dimensional multi-class regression
Generating user interpretable multi-class predictions in data rich envir...
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06/23/2015
Bayesian optimisation for fast approximate inference in state-space models with intractable likelihoods
We consider the problem of approximate Bayesian parameter inference in n...
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06/11/2015
Sparse Partially Collapsed MCMC for Parallel Inference in Topic Models
Topic models, and more specifically the class of Latent Dirichlet Alloca...
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04/16/2014