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Tiangang Cui
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Ano
Dimension-independent likelihood-informed MCMC
T Cui, KJH Law, YM Marzouk
Journal of Computational Physics 304 (1), 109-137, 2016
2332016
Data‐driven model reduction for the Bayesian solution of inverse problems
T Cui, YM Marzouk, KE Willcox
International Journal for Numerical Methods in Engineering 102 (5), 966-990, 2015
2202015
Likelihood-informed dimension reduction for nonlinear inverse problems
T Cui, J Martin, YM Marzouk, A Solonen, A Spantini
Inverse Problems 30 (11), 114015, 2014
2012014
Bayesian calibration of a large‐scale geothermal reservoir model by a new adaptive delayed acceptance Metropolis Hastings algorithm
T Cui, C Fox, MJ O'sullivan
Water Resources Research 47 (10), 2011
1652011
Optimal low-rank approximations of Bayesian linear inverse problems
A Spantini, A Solonen, T Cui, J Martin, L Tenorio, Y Marzouk
SIAM Journal on Scientific Computing 37 (6), A2451–A2487, 2015
1582015
Multifidelity importance sampling
B Peherstorfer, T Cui, Y Marzouk, K Willcox
Computer Methods in Applied Mechanics and Engineering 300, 490-509, 2016
1522016
A Stein variational Newton method
G Detommaso, T Cui, Y Marzouk, A Spantini, R Scheichl
Advances in Neural Information Processing Systems 31, 2018
1452018
Certified dimension reduction in nonlinear Bayesian inverse problems
O Zahm, T Cui, K Law, A Spantini, Y Marzouk
Mathematics of Computation 91 (336), 1789-1835, 2022
992022
Scalable posterior approximations for large-scale Bayesian inverse problems via likelihood-informed parameter and state reduction
T Cui, YM Marzouk, KE Willcox
Journal of Computational Physics 315, 363－387, 2016
712016
Bayesian Inverse Problems with Priors: A Randomize-Then-Optimize Approach
Z Wang, JM Bardsley, A Solonen, T Cui, YM Marzouk
SIAM Journal on Scientific Computing 39 (5), S140-S166, 2017
452017
Goal-oriented optimal approximations of Bayesian linear inverse problems
A Spantini, T Cui, K Willcox, L Tenorio, Y Marzouk
SIAM Journal on Scientific Computing 39 (5), S167-S196, 2017
432017
A posteriori stochastic correction of reduced models in delayed‐acceptance MCMC, with application to multiphase subsurface inverse problems
T Cui, C Fox, MJ O'Sullivan
International Journal for Numerical Methods in Engineering 118 (10), 578-605, 2019
40*2019
Deep composition of Tensor-Trains using squared inverse Rosenblatt transports
T Cui, S Dolgov
Foundations of Computational Mathematics 22 (6), 1863-1922, 2022
362022
Optimization methods for inverse problems
N Ye, F Roosta-Khorasani, T Cui
2017 MATRIX Annals, 121-140, 2019
342019
Data-free likelihood-informed dimension reduction of Bayesian inverse problems
T Cui, O Zahm
Inverse Problems 37 (4), 045009, 2021
332021
A unified performance analysis of likelihood-informed subspace methods
T Cui, XT Tong
Bernoulli 28 (4), 2788-2815, 2022
322022
Extraction of high-resolution structural orientations from digital data: A Bayesian approach
ST Thiele, L Grose, T Cui, AR Cruden, S Micklethwaite
Journal of Structural Geology 122, 106-115, 2019
312019
On dimension reduction in Gaussian filters
A Solonen, T Cui, J Hakkarainen, Y Marzouk
Inverse Problems 32 (4), 045003, 2016
312016
Scalable conditional deep inverse Rosenblatt transports using tensor trains and gradient-based dimension reduction
T Cui, S Dolgov, O Zahm
Journal of Computational Physics 485, 112103, 2023
272023
Scalable optimization-based sampling on function space
JM Bardsley, T Cui, YM Marzouk, Z Wang
SIAM Journal on Scientific Computing 42 (2), A1317-A1347, 2020
242020
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