activity
20222025
most citedUncertainty Quantification for nonparametric regression using Empirical Bayesian neural networks

1 citations · 1 across the 2 of their papers we have counts for

collaborators

3 papers

stat.ME2025

Comment on: "Model uncertainty and missing data: An Objective Bayesian Perspective"

Stefan Franssen

We give a contributed discussion on "Model uncertainty and missing data: An Objective Bayesian Perspective", where we discuss frequentist perspectives on the proposed methodology.

math.ST2024

The Bernstein-von Mises theorem for Semiparametric Mixtures

Stefan Franssen, Jeanne Nguyen, Aad van der Vaart

Semiparametric mixture models are parametric models with latent variables. They are defined kernel, , where z is the unknown latent variable, and is the parameter o…

math.ST2022★ 1 cited

Uncertainty Quantification for nonparametric regression using Empirical Bayesian neural networks

Stefan Franssen, Botond Szabó

We propose a new, two-step empirical Bayes-type of approach for neural networks. We show in context of the nonparametric regression model that the procedure (up to a logarithmic fa…