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1609.05067
Cited By

Asymptotic frequentist coverage properties of Bayesian credible sets for
sieve priors

v1v2v3v4 (latest)

Asymptotic frequentist coverage properties of Bayesian credible sets for sieve priors

16 September 2016

Judith Rousseau

ArXiv (abs)PDF HTML

Papers citing "Asymptotic frequentist coverage properties of Bayesian credible sets for sieve priors"

15 / 15 papers shown

Variational Gaussian Processes For Linear Inverse Problems

Variational Gaussian Processes For Linear Inverse ProblemsNeural Information Processing Systems (NeurIPS), 2023

Thibault Randrianarisoa

341

6

0

01 Nov 2023

The surrogate Gibbs-posterior of a corrected stochastic MALA: Towards uncertainty quantification for neural networks

The surrogate Gibbs-posterior of a corrected stochastic MALA: Towards uncertainty quantification for neural networks

Gregor Kasieczka

Maximilian F. Steffen

369

1

0

13 Oct 2023

Uncertainty quantification for sparse spectral variational
approximations in Gaussian process regression

Uncertainty quantification for sparse spectral variational approximations in Gaussian process regressionElectronic Journal of Statistics (EJS), 2022

Harry Van Zanten

371

6

0

21 Dec 2022

Evidence estimation in finite and infinite mixture models and
applications

Evidence estimation in finite and infinite mixture models and applications

Adrien Hairault

Christian P. Robert

Judith Rousseau

199

2

0

11 May 2022

Optimal recovery and uncertainty quantification for distributed Gaussian
process regression

Optimal recovery and uncertainty quantification for distributed Gaussian process regression

Tammo Hesselink

396

3

0

06 May 2022

Uncertainty Quantification for nonparametric regression using Empirical
Bayesian neural networks

Uncertainty Quantification for nonparametric regression using Empirical Bayesian neural networks

Stefan Franssen

294

5

0

27 Apr 2022

Asymptotically optimal inference in sparse sequence models with a simple
data-dependent measure

Asymptotically optimal inference in sparse sequence models with a simple data-dependent measure

237

0

0

08 Jan 2021

Convergence Rates of Empirical Bayes Posterior Distributions: A
Variational Perspective

Convergence Rates of Empirical Bayes Posterior Distributions: A Variational Perspective

209

4

0

08 Sep 2020

AutoCP: Automated Pipelines for Accurate Prediction Intervals

AutoCP: Automated Pipelines for Accurate Prediction Intervals

266

0

0

24 Jun 2020

Distributed function estimation: adaptation using minimal communication

Distributed function estimation: adaptation using minimal communicationMathematical Statistics and Learning (MSL), 2020

Harry Van Zanten

370

16

0

28 Mar 2020

On frequentist coverage of Bayesian credible sets for estimation of the
mean under constraints

On frequentist coverage of Bayesian credible sets for estimation of the mean under constraints

Johannes Schmidt-Hieber

160

0

0

09 Mar 2020

Can we trust Bayesian uncertainty quantification from Gaussian process
priors with squared exponential covariance kernel?

Can we trust Bayesian uncertainty quantification from Gaussian process priors with squared exponential covariance kernel?

158

19

0

02 Apr 2019

Minimax $L_2$-Separation Rate in Testing the Sobolev-Type Regularity of
a function

L_2

-Separation Rate in Testing the Sobolev-Type Regularity of a function

Maurilio Gutzeit

436

0

0

03 Jan 2019

Adaptive Non-parametric Estimation of Mean and Autocovariance in
Regression with Dependent Errors

Adaptive Non-parametric Estimation of Mean and Autocovariance in Regression with Dependent Errors

Tatyana Krivobokova

Francisco Rosales

Karolina Klockmann

174

2

0

17 Dec 2018

Spike and slab empirical Bayes sparse credible sets

Spike and slab empirical Bayes sparse credible sets

240

21

0

23 Aug 2018

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