5 papers
Semiparametric Bernstein-von Mises theorems for reversible diffusions
Matteo Giordano, Kolyan Ray
We establish a general semiparametric Bernstein-von Mises theorem for Bayesian nonparametric priors based on continuous observations in a periodic reversible multidimensional diffu…
Group Spike and Slab Variational Bayes
Michael Komodromos, Marina Evangelou, Sarah Filippi +1
We introduce Group Spike-and-slab Variational Bayes (GSVB), a scalable method for group sparse regression. A fast co-ordinate ascent variational inference (CAVI) algorithm is devel…
A variational Bayes approach to inference for low-dimensional parameters in high-dimensional linear regression
Ismaël Castillo, Ismaël Castillo, Alice L'Huillier +2
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…
Bayesian Nonparametric Inference in McKean-Vlasov models
Richard Nickl, Grigorios A. Pavliotis, Kolyan Ray
We consider nonparametric statistical inference on a periodic interaction potential from noisy discrete space-time measurements of solutions of the nonlinear McKean-V…
Nonparametric Bayesian estimation in a multidimensional diffusion model with high frequency data
Marc Hoffmann, Kolyan Ray
We consider nonparametric Bayesian inference in a multidimensional diffusion model with reflecting boundary conditions based on discrete high-frequency observations. We prove a gen…