research
∙
06/12/2022
Solving the Poisson equation using coupled Markov chains
This article draws connections between unbiased estimators constructed f...
share
research
∙
10/21/2021
Asymptotics of cut distributions and robust modular inference using Posterior Bootstrap
Bayesian inference provides a framework to combine an arbitrary number o...
research
∙
06/29/2021
Fast Approximation of the Sliced-Wasserstein Distance Using Concentration of Random Projections
The Sliced-Wasserstein distance (SW) is being increasingly used in machi...
research
∙
01/28/2021
Sequential Monte Carlo algorithms for agent-based models of disease transmission
Agent-based models of disease transmission involve stochastic rules that...
research
∙
12/09/2020
Coupled Markov chain Monte Carlo for high-dimensional regression with Half-t priors
Continuous shrinkage priors are commonly used in Bayesian analysis of hi...
research
∙
12/05/2020
A simple Markov chain for independent Bernoulli variables conditioned on their sum
We consider a vector of N independent binary variables, each with a diff...
research
∙
10/16/2020
Maximal couplings of the Metropolis-Hastings algorithm
Couplings play a central role in the analysis of Markov chain Monte Carl...
research
∙
07/23/2020
An invitation to sequential Monte Carlo samplers
Sequential Monte Carlo samplers provide consistent approximations of seq...
research
∙
12/31/2019
Schrödinger Bridge Samplers
Consider a reference Markov process with initial distribution π_0 and tr...
research
∙
10/25/2019
A Gibbs sampler for a class of random convex polytopes
We present a Gibbs sampler to implement the Dempster-Shafer (DS) theory ...
research
∙
05/23/2019
Estimating Convergence of Markov chains with L-Lag Couplings
Markov chain Monte Carlo (MCMC) methods generate samples that are asympt...
research
∙
05/09/2019
Approximate Bayesian computation with the Wasserstein distance
A growing number of generative statistical models do not permit the nume...
research
∙
02/05/2019
Unbiased Smoothing using Particle Independent Metropolis-Hastings
We consider the approximation of expectations with respect to the distri...
research
∙
10/02/2018
Unbiased estimation of log normalizing constants with applications to Bayesian cross-validation
Posterior distributions often feature intractable normalizing constants,...
research
∙
08/23/2018
Adaptive Tuning Of Hamiltonian Monte Carlo Within Sequential Monte Carlo
Sequential Monte Carlo (SMC) samplers form an attractive alternative to ...
research
∙
07/23/2018
Unbiased Markov chain Monte Carlo for intractable target distributions
Performing numerical integration when the integrand itself cannot be eva...
research
∙
09/01/2017
Unbiased Hamiltonian Monte Carlo with couplings
We propose a coupling approach to parallelize Hamiltonian Monte Carlo es...
research
∙
08/11/2017