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09/05/2023
DeepVol: A Deep Transfer Learning Approach for Universal Asset Volatility Modeling
This paper introduces DeepVol, a promising new deep learning volatility ...
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07/21/2023
Adaptively switching between a particle marginal Metropolis-Hastings and a particle Gibbs kernel in SMC^2
Sequential Monte Carlo squared (SMC^2; Chopin et al., 2012) methods can ...
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03/24/2023
Particle Mean Field Variational Bayes
The Mean Field Variational Bayes (MFVB) method is one of the most comput...
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02/21/2023
Bayesian Inference for Evidence Accumulation Models with Regressors
Evidence accumulation models (EAMs) are an important class of cognitive ...
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02/16/2023
Realized recurrent conditional heteroskedasticity model for volatility modelling
We propose a new approach to volatility modelling by combining deep lear...
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02/13/2023
Reliable Bayesian Inference in Misspecified Models
We provide a general solution to a fundamental open problem in Bayesian ...
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02/07/2023
Structured variational approximations with skew normal decomposable graphical models
Although there is much recent work developing flexible variational metho...
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02/02/2023
The Contextual Lasso: Sparse Linear Models via Deep Neural Networks
Sparse linear models are a gold standard tool for interpretable machine ...
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10/06/2022
A correlated pseudo-marginal approach to doubly intractable problems
Doubly intractable models are encountered in a number of fields, e.g. so...
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01/27/2022
Adaptive exact-approximate sequential Monte Carlo
Exact-approximate sequential Monte Carlo (SMC) methods target the exact ...
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09/29/2021
An efficient pseudo marginal method for state space models
Pseudo Marginal Metropolis-Hastings (PMMH) is a general approach to carr...
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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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06/28/2021
Flexible Variational Bayes based on a Copula of a Mixture of Normals
Variational Bayes methods approximate the posterior density by a family ...
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05/04/2021
Modelling age-related changes in executive functions of soccer players
The widespread popularity of soccer across the globe has turned it into ...
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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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04/02/2021
Dynamic models using score copula innovations
This paper introduces a new class of observation driven dynamic models. ...
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02/12/2021
Efficient Selection Between Hierarchical Cognitive Models: Cross-validation With Variational Bayes
Model comparison is the cornerstone of theoretical progress in psycholog...
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10/13/2020
Variational Approximation of Factor Stochastic Volatility Models
Estimation and prediction in high dimensional multivariate factor stocha...
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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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10/16/2019
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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09/17/2019
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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07/25/2019
Particle Methods for Stochastic Differential Equation Mixed Effects Models
Parameter inference for stochastic differential equation mixed effects m...
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06/26/2019
Time-evolving psychological processes over repeated decisions
Many psychological experiments have participants repeat a simple task. T...
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06/14/2019
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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02/13/2019
Bayesian inference using synthetic likelihood: asymptotics and adjustments
Implementing Bayesian inference is often computationally challenging in ...
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09/27/2018
Variance reduction properties of the reparameterization trick
The reparameterization trick is widely used in variational inference as ...
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09/27/2018
On some variance reduction properties of the reparameterization trick
The so-called reparameterization trick is widely used in variational inf...
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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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06/26/2018
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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06/19/2018
Efficient data augmentation for multivariate probit models with panel data: An application to general practitioner decision-making about contraceptives
This article considers the problem of estimating a multivariate probit m...
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05/25/2018
Bayesian Deep Net GLM and GLMM
Deep feedforward neural networks (DFNNs) are a powerful tool for functio...
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05/08/2018
Subsampling Sequential Monte Carlo for Static Bayesian Models
Our article shows how to carry out Bayesian inference by combining data ...
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05/02/2018
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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04/12/2018
Efficiently Combining Pseudo Marginal and Particle Gibbs Sampling
Particle Markov Chain Monte Carlo methods are used to carry out inferenc...
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01/24/2018
Gaussian variational approximation for high-dimensional state space models
Our article considers variational approximations of the posterior distri...
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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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03/27/2016
Exact Subsampling MCMC
Speeding up Markov Chain Monte Carlo (MCMC) for data sets with many obse...
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04/16/2014