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08/21/2023
The Multivariate Bernoulli detector: Change point estimation in discrete survival analysis
Time-to-event data are often recorded on a discrete scale with multiple,...
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07/03/2023
Conditional partial exchangeability: a probabilistic framework for multi-view clustering
Standard clustering techniques assume a common configuration for all fea...
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06/19/2023
Repulsion, Chaos and Equilibrium in Mixture Models
Mixture models are commonly used in applications with heterogeneity and ...
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12/27/2022
Annealing Double-Head: An Architecture for Online Calibration of Deep Neural Networks
Model calibration, which is concerned with how frequently the model pred...
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08/01/2022
Change point detection in dynamic Gaussian graphical models: the impact of COVID-19 pandemic on the US stock market
Reliable estimates of volatility and correlation are fundamental in econ...
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07/27/2022
Bayesian Dynamic Network Modelling: an application to metabolic associations in cardiovascular diseases
We propose a novel approach to the estimation of multiple Graphical Mode...
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05/10/2022
Bayesian clustering of multiple zero-inflated outcomes
Several applications involving counts present a large proportion of zero...
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05/09/2022
On a wider class of prior distributions for graphical models
Gaussian graphical models are useful tools for conditional independence ...
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03/23/2022
Bayesian Nonparametric Vector Autoregressive Models via a Logit Stick-breaking Prior: an Application to Child Obesity
Overweight and obesity in adults are known to be associated with risks o...
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03/22/2022
Bayesian Learning of Graph Substructures
Graphical models provide a powerful methodology for learning the conditi...
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11/11/2021
Integrating metabolic networks and growth biomarkers to unveil potential mechanisms of obesity
The prevalence of chronic non-communicable diseases such as obesity has ...
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08/03/2021
The G-Wishart Weighted Proposal Algorithm: Efficient Posterior Computation for Gaussian Graphical Models
Gaussian graphical models can capture complex dependency structures amon...
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07/12/2021
Cohesion and Repulsion in Bayesian Distance Clustering
Clustering in high-dimensions poses many statistical challenges. While t...
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06/06/2021
Seemingly Unrelated Multi-State processes: a Bayesian semiparametric approach
Many applications in medical statistics as well as in other fields can b...
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03/09/2021
Unbiased approximation of posteriors via coupled particle Markov chain Monte Carlo
Markov chain Monte Carlo (MCMC) is a powerful methodology for the approx...
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05/14/2020
Bayesian Joint Modelling of Recurrence and Survival: a Conditional Approach
Recurrent event processes describe the stochastic repetition of an event...
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10/23/2019
Bayesian nonparametric temporal dynamic clustering via autoregressive Dirichlet priors
In this paper we consider the problem of dynamic clustering, where clust...
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08/12/2019
Bayesian Inference for Latent Chain Graphs
In this article we consider Bayesian inference for partially observed An...
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05/09/2019
On the Efficacy of Monte Carlo Implementation of CAVI
In Variational Inference (VI), coordinate-ascent and gradient-based appr...
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04/22/2019
Is infinity that far? A Bayesian nonparametric perspective of finite mixture models
Mixture models are one of the most widely used statistical tools when de...
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12/04/2018