
Efficient Selection Between Hierarchical Cognitive Models: Crossvalidation With Variational Bayes
Model comparison is the cornerstone of theoretical progress in psycholog...
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Variational Approximation of Factor Stochastic Volatility Models
Estimation and prediction in high dimensional multivariate factor stocha...
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Spectral Subsampling MCMC for Stationary Time Series
Bayesian inference using Markov Chain Monte Carlo (MCMC) on large datase...
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Identifying relationships between cognitive processes across tasks, contexts, and time
It is commonly assumed that a specific testing occasion (task, design, p...
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Multiclass classification of growth curves using random change points and heterogeneous random effects
Faltering growth among children is a nutritional problem prevalent in lo...
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Particle Methods for Stochastic Differential Equation Mixed Effects Models
Parameter inference for stochastic differential equation mixed effects m...
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Timeevolving psychological processes over repeated decisions
Many psychological experiments have participants repeat a simple task. T...
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Robustly estimating the marginal likelihood for cognitive models via importance sampling
Recent advances in Markov chain Monte Carlo (MCMC) extend the scope of B...
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Bayesian inference using synthetic likelihood: asymptotics and adjustments
Implementing Bayesian inference is often computationally challenging in ...
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Variance reduction properties of the reparameterization trick
The reparameterization trick is widely used in variational inference as ...
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On some variance reduction properties of the reparameterization trick
The socalled reparameterization trick is widely used in variational inf...
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Subsampling MCMC  An introduction for the survey statistician
The rapid development of computing power and efficient Markov Chain Mont...
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Subsampling MCMC  A review for the survey statistician
The rapid development of computing power and efficient Markov Chain Mont...
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New Estimation Approaches for the Linear Ballistic Accumulator Model
The Linear Ballistic Accumulator (LBA) model of Brown (2008) is used as ...
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Efficient data augmentation for multivariate probit models with panel data: An application to general practitioner decisionmaking about contraceptives
This article considers the problem of estimating a multivariate probit m...
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Bayesian Deep Net GLM and GLMM
Deep feedforward neural networks (DFNNs) are a powerful tool for functio...
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Subsampling Sequential Monte Carlo for Static Bayesian Models
Our article shows how to carry out Bayesian inference by combining data ...
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Flexible Density Tempering Approaches for State Space Models with an Application to Factor Stochastic Volatility Models
Duan (2015) propose a tempering or annealing approach to Bayesian infere...
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Efficiently Combining Pseudo Marginal and Particle Gibbs Sampling
Particle Markov Chain Monte Carlo methods are used to carry out inferenc...
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Gaussian variational approximation for highdimensional state space models
Our article considers variational approximations of the posterior distri...
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Hamiltonian Monte Carlo with Energy Conserving Subsampling
Hamiltonian Monte Carlo (HMC) has recently received considerable attenti...
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Exact Subsampling MCMC
Speeding up Markov Chain Monte Carlo (MCMC) for data sets with many obse...
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Speeding Up MCMC by Efficient Data Subsampling
We propose Subsampling MCMC, a Markov Chain Monte Carlo (MCMC) framework...
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