research
∙
09/11/2023
Automatic regenerative simulation via non-reversible simulated tempering
Simulated Tempering (ST) is an MCMC algorithm for complex target distrib...
share
research
∙
08/18/2023
Pigeons.jl: Distributed Sampling From Intractable Distributions
We introduce a software package, Pigeons.jl, that provides a way to leve...
research
∙
05/31/2022
Parallel Tempering With a Variational Reference
Sampling from complex target distributions is a challenging task fundame...
research
∙
05/28/2021
Pseudo-marginal Inference for CTMCs on Infinite Spaces via Monotonic Likelihood Approximations
Bayesian inference for Continuous-Time Markov Chains (CTMCs) on countabl...
research
∙
02/15/2021
Parallel Tempering on Optimized Paths
Parallel tempering (PT) is a class of Markov chain Monte Carlo algorithm...
research
∙
06/24/2020
Slice Sampling for General Completely Random Measures
Completely random measures provide a principled approach to creating fle...
research
∙
01/25/2020
Particle-Gibbs Sampling For Bayesian Feature Allocation Models
Bayesian feature allocation models are a popular tool for modelling data...
research
∙
12/22/2019
Blang: Bayesian declarative modelling of arbitrary data structures
Consider a Bayesian inference problem where a variable of interest does ...
research
∙
05/30/2019
Analysis of high-dimensional Continuous Time Markov Chains using the Local Bouncy Particle Sampler
Sampling the parameters of high-dimensional Continuous Time Markov Chain...
research
∙
05/08/2019
Non-Reversible Parallel Tempering: an Embarassingly Parallel MCMC Scheme
Parallel tempering (PT) methods are a popular class of Markov chain Mont...
research
∙
01/28/2019
Scalable Metropolis-Hastings for Exact Bayesian Inference with Large Datasets
Bayesian inference via standard Markov Chain Monte Carlo (MCMC) methods ...
research
∙
06/22/2018
An Annealed Sequential Monte Carlo Method for Bayesian Phylogenetics
The estimation of the probability of the data under a given evolutionary...
research
∙
08/14/2015
Unbounded Bayesian Optimization via Regularization
Bayesian optimization has recently emerged as a popular and efficient to...
research
∙
05/09/2012
