Uncertainty Quantification for nonparametric regression using Empirical Bayesian neural networks

27 April 2022

Papers citing "Uncertainty Quantification for nonparametric regression using Empirical Bayesian neural networks"

9 / 9 papers shown

Title
A Survey of Uncertainty in Deep Neural Networks J. Gawlikowski Cedrique Rovile Njieutcheu Tassi Mohsin Ali Jongseo Lee Matthias Humt ... R. Roscher Muhammad Shahzad Wen Yang R. Bamler Xiaoxiang Zhu BDL UQCV OOD 213 1,146 0 07 Jul 2021
Statistical guarantees for Bayesian uncertainty quantification in non-linear inverse problems with Gaussian process priors F. Monard Richard Nickl G. Paternain 39 35 0 31 Jul 2020
Uncertainty Quantification for Sparse Deep Learning Yuexi Wang Veronika Rockova BDL UQCV 67 31 0 26 Feb 2020
Posterior Concentration for Sparse Deep Learning Nicholas G. Polson Veronika Rockova UQCV BDL 170 88 0 24 Mar 2018
Nonparametric regression using deep neural networks with ReLU activation function Johannes Schmidt-Hieber 212 810 0 22 Aug 2017
Why and When Can Deep -- but Not Shallow -- Networks Avoid the Curse of Dimensionality: a Review T. Poggio H. Mhaskar Lorenzo Rosasco Brando Miranda Q. Liao 97 578 0 02 Nov 2016
Supremum Norm Posterior Contraction and Credible Sets for Nonparametric Multivariate Regression W. Yoo S. Ghosal 64 86 0 25 Nov 2014
Frequentist coverage of adaptive nonparametric Bayesian credible sets Botond Szabó Van der Vaart V. Zanten 77 159 0 16 Oct 2013
On the Bernstein-von Mises phenomenon for nonparametric Bayes procedures I. Castillo Richard Nickl 79 130 0 09 Oct 2013