In a variety of application areas, there is interest in assessing eviden...
In Bayesian inference, the approximation of integrals of the form ψ =
𝔼_...
Sparse structure learning in high-dimensional Gaussian graphical models ...
Proper allocation of law enforcement resources remains a critical issue ...
Marginal likelihood, also known as model evidence, is a fundamental quan...
We consider the class of inverse probability weight (IPW) estimators,
in...
Merging the two cultures of deep and statistical learning provides insig...
The problem of precision matrix estimation in a multivariate Gaussian mo...
While there have been a lot of recent developments in the context of Bay...
Heavy-tailed continuous shrinkage priors, such as the horseshoe prior, a...
Representation Learning in a heterogeneous space with mixed variables of...
Since the advent of the horseshoe priors for regularization, global-loca...
Seemingly unrelated regression is a natural framework for regressing mul...
Feature subset selection arises in many high-dimensional applications of...