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Found 6 papers, 1 papers with code
Mixtures of Gaussian process experts based on kernel stick-breaking processes
Capitalising on the recent advancement in the dependent Dirichlet processes literature, we propose a new mixture model of Gaussian process experts based on kernel stick-breaking processes.
Bayesian structural equation modeling for data from multiple cohorts
In this paper we show how a Bayesian approach can be used to fit a multi-group multi-level structural model that maps cognition to a broad range of observed variables measured at multiple ages.
Applications
Subsampling MCMC - An introduction for the survey statistician
The rapid development of computing power and efficient Markov Chain Monte Carlo (MCMC) simulation algorithms have revolutionized Bayesian statistics, making it a highly practical inference method in applied work.
Subsampling Sequential Monte Carlo for Static Bayesian Models
SMC sequentially updates a cloud of particles through a sequence of distributions, beginning with a distribution that is easy to sample from such as the prior and ending with the posterior distribution.
Hamiltonian Monte Carlo with Energy Conserving Subsampling
The key insight in our article is that efficient subsampling HMC for the parameters is possible if both the dynamics and the acceptance probability are computed from the same data subsample in each complete HMC iteration.
The block-Poisson estimator for optimally tuned exact subsampling MCMC
A pseudo-marginal MCMC method is proposed that estimates the likelihood by data subsampling using a block-Poisson estimator.
