1 citations · 2 across the 3 of their papers we have counts for
3 papers
stat.ML2019★ 1 cited
A New Class of Time Dependent Latent Factor Models with Applications
Sinead A. Williamson, Michael Minyi Zhang, Paul Damien
In many applications, observed data are influenced by some combination of latent causes. For example, suppose sensors are placed inside a building to record responses such as tempe…
stat.ME2014★ 1 cited
Scalable Rejection Sampling for Bayesian Hierarchical Models
Michael Braun, Paul Damien
Bayesian hierarchical modeling is a popular approach to capturing unobserved heterogeneity across individual units. However, standard estimation methods such as Markov chain Monte…
stat.CO2011
Generalized Direct Sampling for Hierarchical Bayesian Models
Michael Braun, Paul Damien
We develop a new method to sample from posterior distributions in hierarchical models without using Markov chain Monte Carlo. This method, which is a variant of importance sampling…