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Sequential Monte Carlo Methods for High-Dimensional Inverse Problems: A
  case study for the Navier-Stokes equations

Sequential Monte Carlo Methods for High-Dimensional Inverse Problems: A case study for the Navier-Stokes equations

23 July 2013
N. Kantas
A. Beskos
Ajay Jasra
ArXivPDFHTML

Papers citing "Sequential Monte Carlo Methods for High-Dimensional Inverse Problems: A case study for the Navier-Stokes equations"

13 / 13 papers shown
Title
Dynamic Term Structure Models with Nonlinearities using Gaussian
  Processes
Dynamic Term Structure Models with Nonlinearities using Gaussian Processes
Tomasz Dubiel-Teleszynski
K. Kalogeropoulos
Nikolaos Karouzakis
14
0
0
18 May 2023
Tensor-train methods for sequential state and parameter learning in
  state-space models
Tensor-train methods for sequential state and parameter learning in state-space models
Yiran Zhao
Tiangang Cui
24
2
0
24 Jan 2023
Generalized Transitional Markov Chain Monte Carlo Sampling Technique for
  Bayesian Inversion
Generalized Transitional Markov Chain Monte Carlo Sampling Technique for Bayesian Inversion
Han Lu
Mohammad Khalil
T. Catanach
Jiefu Chen
Xuqing Wu
Xin Fu
C. Safta
Yueqin Huang
17
0
0
03 Dec 2021
Unbiased approximation of posteriors via coupled particle Markov chain
  Monte Carlo
Unbiased approximation of posteriors via coupled particle Markov chain Monte Carlo
W. van den Boom
Ajay Jasra
M. De Iorio
A. Beskos
J. Eriksson
32
9
0
09 Mar 2021
Deep composition of tensor-trains using squared inverse Rosenblatt
  transports
Deep composition of tensor-trains using squared inverse Rosenblatt transports
Tiangang Cui
S. Dolgov
OT
26
33
0
14 Jul 2020
Consistency analysis of bilevel data-driven learning in inverse problems
Consistency analysis of bilevel data-driven learning in inverse problems
Neil K. Chada
C. Schillings
Xin T. Tong
Simon Weissmann
17
8
0
06 Jul 2020
Generalized Parallel Tempering on Bayesian Inverse Problems
Generalized Parallel Tempering on Bayesian Inverse Problems
J. Latz
Juan P. Madrigal-Cianci
F. Nobile
Raúl Tempone
19
16
0
06 Mar 2020
Bayesian inference of Stochastic reaction networks using Multifidelity
  Sequential Tempered Markov Chain Monte Carlo
Bayesian inference of Stochastic reaction networks using Multifidelity Sequential Tempered Markov Chain Monte Carlo
T. Catanach
Huy D. Vo
B. Munsky
20
12
0
06 Jan 2020
Transform-based particle filtering for elliptic Bayesian inverse
  problems
Transform-based particle filtering for elliptic Bayesian inverse problems
Sangeetika Ruchi
S. Dubinkina
M. Iglesias
OT
11
9
0
15 Jan 2019
Bayesian Updating and Uncertainty Quantification using Sequential
  Tempered MCMC with the Rank-One Modified Metropolis Algorithm
Bayesian Updating and Uncertainty Quantification using Sequential Tempered MCMC with the Rank-One Modified Metropolis Algorithm
T. Catanach
J. Beck
8
10
0
23 Apr 2018
Sequential Monte Carlo Methods for Bayesian Elliptic Inverse Problems
Sequential Monte Carlo Methods for Bayesian Elliptic Inverse Problems
A. Beskos
Ajay Jasra
Ege A. Muzaffer
Andrew M. Stuart
26
72
0
15 Dec 2014
A Stable Particle Filter in High-Dimensions
A Stable Particle Filter in High-Dimensions
A. Beskos
Dan Crisan
Ajay Jasra
K. Kamatani
Yan Zhou
40
35
0
11 Dec 2014
On the Convergence of Adaptive Sequential Monte Carlo Methods
On the Convergence of Adaptive Sequential Monte Carlo Methods
A. Beskos
Ajay Jasra
N. Kantas
Alexandre Hoang Thiery
33
92
0
27 Jun 2013
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