Tiangang Cui

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Youssef MarzoukProfessor, Massachusetts Institute of TechnologyVerified email at mit.edu
Colin FoxUniversity of OtagoVerified email at otago.ac.nz
Karen WillcoxOden Institute for Computational Engineering and Sciences, UT AustinVerified email at oden.utexas.edu
Alessio SpantiniMassachusetts Institute of TechnologyVerified email at mit.edu
Michael OSullivanProfessor of Engineering Science, University of AucklandVerified email at aucklanduni.ac.nz
Antti SolonenResearcher, laboratory of applied mathematics, Lappeenranta University of TechnologyVerified email at lut.fi
Johnathan M. BardsleyProfessor of Mathematics, University of MontanaVerified email at mso.umt.edu
Olivier ZahmINRIAVerified email at inria.fr
Kody J. H. LawDepartment of Mathematics, University of ManchesterVerified email at manchester.ac.uk
Robert ScheichlHeidelberg UniversityVerified email at uni-heidelberg.de
James MartinInstitute for Computational Engineering and Sciences, UT AustinVerified email at ices.utexas.edu
Gianluca DetommasoSenior Applied Scientist, AWSVerified email at amazon.com
Sergey DolgovUniversity of BathVerified email at bath.ac.uk
Benjamin PeherstorferCourant Institute of Mathematical Sciences, New York UniversityVerified email at cims.nyu.edu
Xin T. TongNational University of SingaporeVerified email at nus.edu.sg
Geoff NichollsAssociate Professor of Statistics, University of OxfordVerified email at stats.ox.ac.uk
Nan YeLecturer, University of QueenslandVerified email at uq.edu.au
Fred RoostaUniversity of QueenslandVerified email at uq.edu.au
Hans De SterckProfessor, Computational and Applied Mathematics, University of WaterlooVerified email at uwaterloo.ca
Siyuan WuLecturer (Computational Biology) at James Cook UniversityVerified email at jcu.edu.au

Tiangang Cui

University of Sydney

Verified email at sydney.edu.au - Homepage

Inverse problem Data Assimilation MCMC Subsurface Modeling


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
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	197	2015
Dimension-independent likelihood-informed MCMC T Cui, KJH Law, YM Marzouk Journal of Computational Physics 304 (1), 109-137, 2016	196	2016
Likelihood-informed dimension reduction for nonlinear inverse problems T Cui, J Martin, YM Marzouk, A Solonen, A Spantini Inverse Problems 30 (11), 114015, 2014	165	2014
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	148	2011
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	130	2015
Multifidelity importance sampling B Peherstorfer, T Cui, Y Marzouk, K Willcox Computer Methods in Applied Mechanics and Engineering 300, 490-509, 2016	123	2016
A Stein variational Newton method G Detommaso, T Cui, Y Marzouk, A Spantini, R Scheichl Advances in Neural Information Processing Systems 31, 2018	120	2018
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	73*	2022
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	56	2016
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	38	2017
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	37*	2019
Optimization methods for inverse problems N Ye, F Roosta-Khorasani, T Cui 2017 MATRIX Annals, 121-140, 2019	29	2019
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	28	2017
On dimension reduction in Gaussian filters A Solonen, T Cui, J Hakkarainen, Y Marzouk Inverse Problems 32 (4), 045003, 2016	22	2016
Deep composition of Tensor-Trains using squared inverse Rosenblatt transports T Cui, S Dolgov Foundations of Computational Mathematics 22 (6), 1863-1922, 2022	21	2022
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	20	2020
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	18	2019
Bayesian calibration of geothermal reservoir models via Markov Chain Monte Carlo T Cui PhD Thesis-University of Auckland, 2010	18	2010
Data-free likelihood-informed dimension reduction of Bayesian inverse problems T Cui, O Zahm Inverse Problems 37 (4), 045009, 2021	16	2021
A unified performance analysis of likelihood-informed subspace methods T Cui, XT Tong Bernoulli 28 (4), 2788-2815, 2022	15	2022

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