Deep Gaussian Process Priors for Bayesian Inference in Nonlinear Inverse Problems

21 December 2023

Papers citing "Deep Gaussian Process Priors for Bayesian Inference in Nonlinear Inverse Problems"

11 / 11 papers shown

Title
Deep Horseshoe Gaussian Processes Ismael Castillo Thibault Randrianarisoa BDL UQCV 80 5 0 04 Mar 2024
On the inability of Gaussian process regression to optimally learn compositional functions M. Giordano Kolyan Ray Johannes Schmidt-Hieber 89 13 0 16 May 2022
Deep Gaussian Processes for Biogeophysical Parameter Retrieval and Model Inversion D. Svendsen Pablo Morales-Álvarez A. Ruescas Rafael Molina Gustau Camps-Valls 118 30 0 16 Apr 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
Consistency of Bayesian inference with Gaussian process priors in an elliptic inverse problem M. Giordano Richard Nickl 60 59 0 16 Oct 2019
Consistent Inversion of Noisy Non-Abelian X-Ray Transforms F. Monard Richard Nickl G. Paternain 32 58 0 02 May 2019
Convergence rates for Penalised Least Squares Estimators in PDE-constrained regression problems Richard Nickl Sara van de Geer Sven Wang 34 60 0 24 Sep 2018
Nonparametric regression using deep neural networks with ReLU activation function Johannes Schmidt-Hieber 216 810 0 22 Aug 2017
Geometric MCMC for Infinite-Dimensional Inverse Problems A. Beskos Mark Girolami Shiwei Lan P. Farrell Andrew M. Stuart 48 143 0 20 Jun 2016
Deep Gaussian Processes Andreas C. Damianou Neil D. Lawrence GP BDL 120 1,181 0 02 Nov 2012
MCMC Methods for Functions: Modifying Old Algorithms to Make Them Faster S. Cotter Gareth O. Roberts Andrew M. Stuart D. White 97 480 0 03 Feb 2012