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A randomized maximum a posterior method for posterior sampling of high
  dimensional nonlinear Bayesian inverse problems

A randomized maximum a posterior method for posterior sampling of high dimensional nonlinear Bayesian inverse problems

11 February 2016
Kainan Wang
T. Bui-Thanh
Omar Ghattas
ArXivPDFHTML

Papers citing "A randomized maximum a posterior method for posterior sampling of high dimensional nonlinear Bayesian inverse problems"

12 / 12 papers shown
Title
Can Diffusion Models Provide Rigorous Uncertainty Quantification for Bayesian Inverse Problems?
Evan Scope Crafts
Umberto Villa
44
0
0
04 Mar 2025
Randomized Physics-Informed Neural Networks for Bayesian Data
  Assimilation
Randomized Physics-Informed Neural Networks for Bayesian Data Assimilation
Yifei Zong
D. Barajas-Solano
A. Tartakovsky
46
1
0
05 Jul 2024
Randomized Physics-Informed Machine Learning for Uncertainty
  Quantification in High-Dimensional Inverse Problems
Randomized Physics-Informed Machine Learning for Uncertainty Quantification in High-Dimensional Inverse Problems
Yifei Zong
D. Barajas-Solano
A. Tartakovsky
27
2
0
11 Dec 2023
VI-DGP: A variational inference method with deep generative prior for
  solving high-dimensional inverse problems
VI-DGP: A variational inference method with deep generative prior for solving high-dimensional inverse problems
Yingzhi Xia
Qifeng Liao
Jinglai Li
19
2
0
22 Feb 2023
Variational Inference for Nonlinear Inverse Problems via Neural Net
  Kernels: Comparison to Bayesian Neural Networks, Application to Topology
  Optimization
Variational Inference for Nonlinear Inverse Problems via Neural Net Kernels: Comparison to Bayesian Neural Networks, Application to Topology Optimization
Vahid Keshavarzzadeh
Robert M. Kirby
A. Narayan
BDL
11
2
0
07 May 2022
Conditional Injective Flows for Bayesian Imaging
Conditional Injective Flows for Bayesian Imaging
AmirEhsan Khorashadizadeh
K. Kothari
Leonardo Salsi
Ali Aghababaei Harandi
Maarten V. de Hoop
Ivan Dokmanić
MedIm
21
16
0
15 Apr 2022
Randomized maximum likelihood based posterior sampling
Randomized maximum likelihood based posterior sampling
Yuming Ba
Jana de Wiljes
D. Oliver
Sebastian Reich
12
7
0
10 Jan 2021
Optimization-Based MCMC Methods for Nonlinear Hierarchical Statistical
  Inverse Problems
Optimization-Based MCMC Methods for Nonlinear Hierarchical Statistical Inverse Problems
Johnathan M. Bardsley
Tiangang Cui
6
1
0
15 Feb 2020
hIPPYlib: An Extensible Software Framework for Large-Scale Inverse
  Problems Governed by PDEs; Part I: Deterministic Inversion and Linearized
  Bayesian Inference
hIPPYlib: An Extensible Software Framework for Large-Scale Inverse Problems Governed by PDEs; Part I: Deterministic Inversion and Linearized Bayesian Inference
Umberto Villa
N. Petra
Omar Ghattas
8
61
0
09 Sep 2019
Scalable optimization-based sampling on function space
Scalable optimization-based sampling on function space
Johnathan M. Bardsley
Tiangang Cui
Youssef Marzouk
Zheng Wang
27
17
0
03 Mar 2019
Metropolized Randomized Maximum Likelihood for sampling from multimodal
  distributions
Metropolized Randomized Maximum Likelihood for sampling from multimodal distributions
D. Oliver
13
30
0
30 Jul 2015
MCMC using Hamiltonian dynamics
MCMC using Hamiltonian dynamics
Radford M. Neal
176
3,260
0
09 Jun 2012
1