Despite major methodological developments, Bayesian inference in Gaussian graphical models remains challenging in high dimension due to the tremendous size of the model space. This article proposes a ...

Functional data are defined as realizations of random functions (mostly smooth functions) varying over a continuum, which are usually collected on discretized grids with measurement errors. In order ...

Data really powers everything that we do. Research activities in the data science area are concerned with the development of machine learning and computational statistical methods, their theoretical ...

In the ever-evolving toolkit of statistical analysis techniques, Bayesian statistics has emerged as a popular and powerful methodology for making decisions from data in the applied sciences. Bayesian ...

Data really powers everything that we do. Research activities in the data science area are concerned with the development of machine learning and computational statistical methods, their theoretical ...