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Slice Sampling for General Completely Random Measures
Completely random measures provide a principled approach to creating fle...
06/24/2020 ∙ by Peiyuan Zhu, et al. ∙
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Particle-Gibbs Sampling For Bayesian Feature Allocation Models
Bayesian feature allocation models are a popular tool for modelling data...
01/25/2020 ∙ by Alexandre Bouchard-Côté, et al. ∙
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Blang: Bayesian declarative modelling of arbitrary data structures
Consider a Bayesian inference problem where a variable of interest does ...
12/22/2019 ∙ by Alexandre Bouchard-Côté, et al. ∙
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Analysis of high-dimensional Continuous Time Markov Chains using the Local Bouncy Particle Sampler
Sampling the parameters of high-dimensional Continuous Time Markov Chain...
05/30/2019 ∙ by Tingting Zhao, et al. ∙
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Non-Reversible Parallel Tempering: an Embarassingly Parallel MCMC Scheme
Parallel tempering (PT) methods are a popular class of Markov chain Mont...
05/08/2019 ∙ by Saifuddin Syed, et al. ∙
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Scalable Metropolis-Hastings for Exact Bayesian Inference with Large Datasets
Bayesian inference via standard Markov Chain Monte Carlo (MCMC) methods ...
01/28/2019 ∙ by Robert Cornish, et al. ∙
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An Annealed Sequential Monte Carlo Method for Bayesian Phylogenetics
The estimation of the probability of the data under a given evolutionary...
06/22/2018 ∙ by Liangliang Wang, et al. ∙
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Unbounded Bayesian Optimization via Regularization
Bayesian optimization has recently emerged as a popular and efficient to...
08/14/2015 ∙ by Bobak Shahriari, et al. ∙
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Optimization of Structured Mean Field Objectives
In intractable, undirected graphical models, an intuitive way of creatin...
05/09/2012 ∙ by Alexandre Bouchard-Côté, et al. ∙
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