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

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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…