280 citations · 916 across the 24 of their papers we have counts for
30 papers
Multiple testing with the horseshoe
Sayantan Banerjee, Ismaël Castillo, Fanny Villers
We study multiple testing under continuous global--local shrinkage priors, with a focus on the horseshoe prior in high-dimensional sparse settings. While such priors provide adapti…
A variational Bayes approach to inference for low-dimensional parameters in high-dimensional linear regression
Ismaël Castillo, Alice L'Huillier, Kolyan Ray +1
We propose a scalable variational Bayes method for statistical inference for a single or pre-specified low-dimensional subset of the coordinates of a high-dimensional parameter in…
Deep Horseshoe Gaussian Processes
Ismaël Castillo, Thibault Randrianarisoa
Deep Gaussian processes have recently been proposed as natural objects to fit, similarly to deep neural networks, possibly complex features present in modern data samples, such as…
Bayesian nonparametric statistics, St-Flour lecture notes
Ismaël Castillo
These are lecture notes of the 51st Saint-Flour summer school, July 2023, on the topic of Bayesian nonparametric statistics
Heavy-tailed Bayesian nonparametric adaptation
Sergios Agapiou, Ismaël Castillo
We propose a new Bayesian strategy for adaptation to smoothness in nonparametric models based on heavy tailed series priors. We illustrate it in a variety of settings, showing in p…
Semiparametric inference using fractional posteriors
Alice L'Huillier, Luke Travis, Ismaël Castillo +1
We establish a general Bernstein--von Mises theorem for approximately linear semiparametric functionals of fractional posterior distributions based on nonparametric priors. This is…