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01/08/2023
Skewed Bernstein-von Mises theorem and skew-modal approximations
Deterministic Gaussian approximations of intractable posterior distribut...
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09/24/2022
Learning and forecasting of age-specific period mortality via B-spline processes with locally-adaptive dynamic coefficients
The overarching focus on predictive accuracy in mortality forecasting ha...
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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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06/14/2022
Concentration and robustness of discrepancy-based ABC via Rademacher complexity
Classical implementations of approximate Bayesian computation (ABC) empl...
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09/25/2020
Bayesian Testing for Exogenous Partition Structures in Stochastic Block Models
Network data often exhibit block structures characterized by clusters of...
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09/03/2020
Scalable computation of predictive probabilities in probit models with Gaussian process priors
Predictive models for binary data are fundamental in various fields, and...
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07/16/2020
Extended Stochastic Block Models
Stochastic block models (SBM) are widely used in network science due to ...
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07/14/2020
A Class of Conjugate Priors for Multinomial Probit Models which Includes the Multivariate Normal One
Multinomial probit models are widely-implemented representations which a...
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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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02/19/2019
Exact Kalman Filter for Binary Time Series
Non-Gaussian state-space models arise routinely in several applications....
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02/12/2019
Bayesian cumulative shrinkage for infinite factorizations
There are a variety of Bayesian models relying on representations in whi...
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02/26/2018
Conjugate Bayes for probit regression via unified skew-normals
Regression models for dichotomous data are ubiquitous in statistics. Bes...
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11/19/2017
A note on quadratic approximations of logistic log-likelihoods
Quadratic approximations of logistic log-likelihoods are fundamental to ...
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08/07/2016
Bayesian Learning of Dynamic Multilayer Networks
A plethora of networks is being collected in a growing number of fields,...
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05/21/2015
Locally Adaptive Dynamic Networks
Our focus is on realistically modeling and forecasting dynamic networks ...
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11/19/2013
Nonparametric Bayes dynamic modeling of relational data
Symmetric binary matrices representing relations among entities are comm...
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10/07/2012