Convergence Rates for the Maximum A Posteriori Estimator in
PDE-Regression Models with Random Design

Convergence Rates for the Maximum A Posteriori Estimator in PDE-Regression Models with Random Design

5 September 2024

Maximilian Siebel

Papers citing "Convergence Rates for the Maximum A Posteriori Estimator in PDE-Regression Models with Random Design"

7 / 7 papers shown

Title
Bayesian Nonparametric Inference in McKean-Vlasov models Richard Nickl G. Pavliotis Kolyan Ray 36 5 0 25 Apr 2024
On posterior consistency of data assimilation with Gaussian process priors: the 2D Navier-Stokes equations Richard Nickl E. Titi 22 7 0 16 Jul 2023
Estimation for the reaction term in semi-linear SPDEs under small diffusivity Sascha Gaudlitz M. Reiß 47 18 0 20 Mar 2022
On polynomial-time computation of high-dimensional posterior measures by Langevin-type algorithms Richard Nickl Sven Wang 39 40 0 11 Sep 2020
Statistical guarantees for Bayesian uncertainty quantification in non-linear inverse problems with Gaussian process priors F. Monard Richard Nickl G. Paternain 49 35 0 31 Jul 2020
Consistency of Bayesian inference with Gaussian process priors in an elliptic inverse problem M. Giordano Richard Nickl 68 60 0 16 Oct 2019
Convergence rates for Penalised Least Squares Estimators in PDE-constrained regression problems Richard Nickl Sara van de Geer Sven Wang 40 60 0 24 Sep 2018