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04/14/2023
Complexity of Gibbs samplers through Bayesian asymptotics
Gibbs samplers are popular algorithms to approximate posterior distribut...
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11/21/2022
Improving multiple-try Metropolis with local balancing
Multiple-try Metropolis (MTM) is a popular Markov chain Monte Carlo meth...
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09/19/2022
Robust leave-one-out cross-validation for high-dimensional Bayesian models
Leave-one-out cross-validation (LOO-CV) is a popular method for estimati...
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06/16/2022
Bayesian conjugacy in probit, tobit, multinomial probit and extensions: A review and new results
A broad class of models that routinely appear in several fields can be e...
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05/25/2022
Clustering consistency with Dirichlet process mixtures
Dirichlet process mixtures are flexible non-parametric models, particula...
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01/04/2022
Optimal design of the Barker proposal and other locally-balanced Metropolis-Hastings algorithms
We study the class of first-order locally-balanced Metropolis–Hastings a...
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03/19/2021
Scalable computation for Bayesian hierarchical models
The article is about algorithms for learning Bayesian hierarchical model...
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12/17/2020
A fresh take on 'Barker dynamics' for MCMC
We study a recently introduced gradient-based Markov chain Monte Carlo m...
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04/04/2020
Random Partition Models for Microclustering Tasks
Traditional Bayesian random partition models assume that the size of eac...
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11/15/2019
Scalable and Accurate Variational Bayes for High-Dimensional Binary Regression Models
State-of-the-art methods for Bayesian inference on regression models wit...
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11/15/2019
Asymptotically Exact Variational Bayes for High-Dimensional Binary Regression Models
State-of-the-art methods for Bayesian inference on regression models wit...
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08/30/2019
On the robustness of gradient-based MCMC algorithms
We analyse the tension between robustness and efficiency for Markov chai...
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05/01/2018
Scalable Importance Tempering and Bayesian Variable Selection
We propose a Monte Carlo algorithm to sample from high-dimensional proba...
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03/26/2018
Scalable inference for crossed random effects models
We analyze the complexity of Gibbs samplers for inference in crossed ran...
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11/20/2017
Informed proposals for local MCMC in discrete spaces
There is a lack of methodological results to design efficient Markov cha...
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09/04/2017
Unbiased approximations of products of expectations
We consider the problem of approximating the product of n expectations w...
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10/31/2016
