Fetching the paper…
Reading the bibliography…
We consider Bayesian inference for large scale inverse problems, where computational challenges arise from the need for repeated evaluations of an expensive forward model.
A new approach to linear filtering and prediction problems
Rudolph Emil Kalman · 1960
Earlier work this paper cites.
Numerical analysis of blood flow in the heart
Charles S Peskin · 1977
Earlier work this paper cites.
Brownian dynamics as smart Monte Carlo simulation
Peter J Rossky, Jimmie D Doll, and Harold L Friedman · 1978
Earlier work this paper cites.
Kalman filtering: Theory and application
Harold Wayne Sorenson · 1985
Earlier work this paper cites.
A mean field theory learning algorithm for neural networks
James R Anderson and Carsten Peterson · 1987
Earlier work this paper cites.
Introduction to seismic inversion methods
Brian H Russell · 1988
Earlier work this paper cites.
Statistical field theory
Giorgio Parisi and Ramamurti Shankar · 1988
Earlier work this paper cites.
Local adaptive mesh refinement for shock hydrodynamics
Marsha J Berger, Phillip Colella, et al · 1989
Earlier work this paper cites.
Practical Markov chain Monte Carlo
Charles J Geyer · 1992
Earlier work this paper cites.
Kalman filtering with random coefficients and contractions
Philippe Bougerol · 1993
Earlier work this paper cites.
Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics
Geir Evensen · 1994
Earlier work this paper cites.
A proposal for the intercomparison of the dynamical cores of atmospheric general circulation models
Isaac M Held and Max J Suarez · 1994
Earlier work this paper cites.
Multiscale seismic waveform inversion
Carey Bunks, Fatimetou M Saleck, S Zaleski, and G Chavent · 1995
Earlier work this paper cites.
A new approach for filtering nonlinear systems
Simon J Julier, Jeffrey K Uhlmann, and Hugh F Durrant-Whyte · 1995
Earlier work this paper cites.
Algebraic Riccati equations
Peter Lancaster and Leiba Rodman · 1995
Earlier work this paper cites.
Exponential convergence of Langevin distributions and their discrete approximations
Gareth O Roberts and Richard L Tweedie · 1996
Earlier work this paper cites.
Weak convergence and optimal scaling of random walk Metropolis algorithms
Andrew Gelman, Walter R Gilks, and Gareth O Roberts · 1997
Earlier work this paper cites.
A finite element method for crack growth without remeshing
Nicolas Moës, John Dolbow, and Ted Belytschko · 1999
Earlier work this paper cites.
The unscented Kalman filter for nonlinear estimation
Eric A Wan and Rudolph Van Der Merwe · 2000
Earlier work this paper cites.
An ensemble adjustment Kalman filter for data assimilation
Jeffrey L Anderson · 2001
Earlier work this paper cites.
Adaptive sampling with the ensemble transform Kalman filter. Part I: Theoretical aspects
Craig H Bishop, Brian J Etherton, and Sharanya J Majumdar · 2001
Earlier work this paper cites.
Multilevel Monte Carlo methods
Stefan Heinrich · 2001
Earlier work this paper cites.
Reduced sigma point filters for the propagation of means and covariances through nonlinear transformations
Simon J Julier and Jeffrey K Uhlmann · 2002
Earlier work this paper cites.
Ensemble square root filters
Michael K Tippett, Jeffrey L Anderson, Craig H Bishop, Thomas M Hamill, and Jeffrey S Whitaker · 2003
Earlier work this paper cites.
A comparison of breeding and ensemble transform Kalman filter ensemble forecast schemes
Xuguang Wang and Craig H Bishop · 2003
Earlier work this paper cites.
Stochastic finite elements: a spectral approach
Roger G Ghanem and Pol D Spanos · 2003
Earlier work this paper cites.
Sequential Monte Carlo samplers
Pierre Del Moral, Arnaud Doucet, and Ajay Jasra · 2006
Earlier work this paper cites.
Statistical and computational inverse problems
Jari Kaipio and Erkki Somersalo · 2006
Earlier work this paper cites.
OpenFOAM: A C++ library for complex physics simulations
Hrvoje Jasak, Aleksandar Jemcov, Zeljko Tukovic, et al · 2007
Earlier work this paper cites.
Stochastic processes and filtering theory
Andrew H Jazwinski · 2007
Earlier work this paper cites.
An adaptive covariance inflation error correction algorithm for ensemble filters
Jeffrey L Anderson · 2007
Earlier work this paper cites.
Inverse theory for petroleum reservoir characterization and history matching
Dean S Oliver, Albert C Reynolds, and Ning Liu · 2008
Earlier work this paper cites.
The variational Gaussian approximation revisited
Manfred Opper and Cédric Archambeau · 2009
Earlier work this paper cites.
Accelerating Markov chain Monte Carlo simulation by differential evolution with self-adaptive randomized subspace sampling
Jasper A Vrugt, CJF Ter Braak, CGH Diks, Bruce A Robinson, James M Hyman, and Dave Higdon · 2009
Earlier work this paper cites.
The ensemble Kalman filter for combined state and parameter estimation
Geir Evensen · 2009
Earlier work this paper cites.
Data assimilation: The ensemble Kalman filter
Geir Evensen · 2009
Earlier work this paper cites.
Ensemble samplers with affine invariance
Jonathan Goodman and Jonathan Weare · 2010
Earlier work this paper cites.
Inverse problems: A Bayesian perspective
Andrew M Stuart · 2010
Cited alongside, same era.
Reduced-order unscented Kalman filtering with application to parameter identification in large-dimensional systems
Philippe Moireau and Dominique Chapelle · 2011
Cited alongside, same era.
A dynamical systems framework for intermittent data assimilation
Sebastian Reich · 2011
Cited alongside, same era.
Spectral numerical weather prediction models
Martin Ehrendorfer · 2011
Cited alongside, same era.
A stochastic Newton MCMC method for large-scale statistical inverse problems with application to seismic inversion
James Martin, Lucas C Wilcox, Carsten Burstedde, and Omar Ghattas · 2012
Cited alongside, same era.
Sequential parameter estimation for fluid–structure problems: Application to hemodynamics
Cristóbal Bertoglio, Philippe Moireau, and Jean-Frederic Gerbeau · 2012
Ensemble preconditioning for Markov chain Monte Carlo simulations
Benedict Leimkuhler, Charles Matthews, and Jonathan Weare · 2018
Later among the works it cites.
An analytical framework for consensus-based global optimization method
José A Carrillo, Young-Pil Choi, Claudia Totzeck, and Oliver Tse · 2018
Later among the works it cites.
Inverse problems and data assimilation
Daniel Sanz-Alonso, Andrew M Stuart, and Armeen Taeb · 2018
Later among the works it cites.
Kinetic methods for inverse problems
Michael Herty and Giuseppe Visconti · 2018
Later among the works it cites.
Mesh adaptation framework for embedded boundary methods for computational fluid dynamics and fluid-structure interaction
Raunak Borker, Daniel Huang, Sebastian Grimberg, Charbel Farhat, Philip Avery, and Jason Rabinovitch · 2019
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Bayesian inference with optimal maps
Tarek A El Moselhy and Youssef M Marzouk · 2012
Cited alongside, same era.
Ensemble randomized maximum likelihood method as an iterative ensemble smoother
Yan Chen and Dean S Oliver · 2012
Cited alongside, same era.
Global optimization methods in geophysical inversion
Mrinal K Sen and Paul L Stoffa · 2013
Cited alongside, same era.
A computational framework for infinite-dimensional Bayesian inverse problems. Part I: The linearized case, with application to global seismic inversion
Tan Bui-Thanh, Omar Ghattas, James Martin, and Georg Stadler · 2013
Cited alongside, same era.
MCMC methods for functions: Modifying old algorithms to make them faster
Simon L Cotter, Gareth O Roberts, Andrew M Stuart, and David White · 2013
Cited alongside, same era.
The Bayesian approach to inverse problems
Masoumeh Dashti and Andrew M Stuart · 2013
Cited alongside, same era.
Transform-based particle filtering for elliptic Bayesian inverse problems
Sangeetika Ruchi, Svetlana Dubinkina, and MA Iglesias · 2019
Later among the works it cites.
Nikolas Nüsken and Sebastian Reich · 2019
Later among the works it cites.
Ensemble Kalman methods with constraints
David J Albers, Paul-Adrien Blancquart, Matthew E Levine, Elnaz Esmaeilzadeh Seylabi, and Andrew Stuart · 2019
Later among the works it cites.
On the incorporation of box-constraints for ensemble kalman inversion
Neil K Chada, Claudia Schillings, and Simon Weissmann · 2019
Later among the works it cites.
Learning constitutive relations from indirect observations using deep neural networks
Daniel Z Huang, Kailai Xu, Charbel Farhat, and Eric Darve · 2020
Later among the works it cites.
Modeling, simulation and validation of supersonic parachute inflation dynamics during Mars landing
Daniel Z Huang, Philip Avery, Charbel Farhat, Jason Rabinovitch, Armen Derkevorkian, and Lee D Peterson · 2020
Later among the works it cites.
Tikhonov regularization within ensemble Kalman inversion
Neil K Chada, Andrew M Stuart, and Xin T Tong · 2020
Later among the works it cites.
Interacting Langevin diffusions: Gradient structure and ensemble Kalman sampler
Alfredo Garbuno-Inigo, Franca Hoffmann, Wuchen Li, and Andrew M Stuart · 2020
Later among the works it cites.
Affine invariant interacting Langevin dynamics for Bayesian inference
Alfredo Garbuno-Inigo, Nikolas Nüsken, and Sebastian Reich · 2020
Later among the works it cites.
Bi-fidelity approximation for uncertainty quantification and sensitivity analysis of irradiated particle-laden turbulence
Hillary R Fairbanks, Lluís Jofre, Gianluca Geraci, Gianluca Iaccarino, and Alireza Doostan · 2020
Later among the works it cites.
Multilevel ensemble kalman-bucy filters
Neil K Chada, Ajay Jasra, and Fangyuan Yu · 2020
Later among the works it cites.
Ensemble Kalman inversion for sparse learning of dynamical systems from time-averaged data
Tapio Schneider, Andrew M Stuart, and Jin-Long Wu · 2020
Later among the works it cites.
Ensemble Kalman inversion for nonlinear problems: Weights, consistency, and variance bounds
Zhiyan Ding, Qin Li, and Jianfeng Lu · 2020
Later among the works it cites.
Learning constitutive relations using symmetric positive definite neural networks
Kailai Xu, Daniel Z Huang, and Eric Darve · 2021
Later among the works it cites.
A computationally tractable framework for nonlinear dynamic multiscale modeling of membrane woven fabrics
Philip Avery, Daniel Z Huang, Wanli He, Johanna Ehlers, Armen Derkevorkian, and Charbel Farhat · 2021
Later among the works it cites.
Flexible and efficient inference with particles for the variational Gaussian approximation
Théo Galy-Fajou, Valerio Perrone, and Manfred Opper · 2021
Later among the works it cites.
Consensus-based sampling
JA Carrillo, F Hoffmann, AM Stuart, and U Vaes · 2021
Later among the works it cites.
Affine-invariant ensemble transform methods for logistic regression
Jakiw Pidstrigach and Sebastian Reich · 2021
Later among the works it cites.
Adaptive regularisation for ensemble Kalman inversion
Marco Iglesias and Yuchen Yang · 2021
Later among the works it cites.
Bayesian inversion algorithm for estimating local variations in permeability and porosity of reinforcements using experimental data
MY Matveev, A Endruweit, AC Long, MA Iglesias, and MV Tretyakov · 2021
Later among the works it cites.
Efficient multiscale imaging of subsurface resistivity with uncertainty quantification using ensemble Kalman inversion
Chak-Hau Michael Tso, Marco Iglesias, Paul Wilkinson, Oliver Kuras, Jonathan Chambers, and Andrew Binley · 2021
Later among the works it cites.
Daniel Z Huang, Tapio Schneider, and Andrew M Stuart · 2021
Later among the works it cites.
A unified performance analysis of likelihood-informed subspace methods
Tiangang Cui and Xin T Tong · 2021
Later among the works it cites.
A bi-fidelity ensemble Kalman method for PDE-constrained inverse problems in computational mechanics
Han Gao and Jian-Xun Wang · 2021
Later among the works it cites.
JA Carrillo, C Totzeck, and U Vaes · 2021
Later among the works it cites.
A consensus-based global optimization method for high dimensional machine learning problems
José A Carrillo, Shi Jin, Lei Li, and Yuhua Zhu · 2021
Later among the works it cites.
LongLong Wang · 2022
Closest in time.
Bayesian calibration for large-scale fluid structure interaction problems under embedded/immersed boundary framework
Shunxiang Cao and Daniel Zhengyu Huang · 2022
Closest in time.
Training physics-based machine-learning parameterizations with gradient-free ensemble kalman methods
Ignacio Lopez-Gomez, Costa D Christopoulos, Haakon Ludvig Ervik, Oliver R Dunbar, Yair Cohen, and Tapio Schneider · 2022
Closest in time.
Adaptive Tikhonov strategies for stochastic ensemble Kalman inversion
Simon Weissmann, Neil Kumar Chada, Claudia Schillings, and Xin Thomson Tong · 2022
Closest in time.
Ensemble Kalman methods: A mean field perspective
Edoardo Calvello, Sebastian Reich, and Andrew M Stuart · 2022
Closest in time.