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
Olivier ZahmINRIAVerified email at inria.fr
Antti SolonenResearcher, laboratory of applied mathematics, Lappeenranta University of TechnologyVerified email at lut.fi
Robert ScheichlHeidelberg UniversityVerified email at uni-heidelberg.de
Johnathan M. BardsleyProfessor of Mathematics, University of MontanaVerified email at mso.umt.edu
Kody J. H. LawProfessor at the University of Manchester and AI Research Scientist at MetaVerified email at meta.com
Gianluca DetommasoAI Research at Helsing | ex-AWSVerified email at helsing.ai
James MartinInstitute for Computational Engineering and Sciences, UT AustinVerified email at ices.utexas.edu
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
Hans De SterckProfessor, Computational and Applied Mathematics, University of WaterlooVerified email at uwaterloo.ca
Nan YeLecturer, University of QueenslandVerified email at uq.edu.au
Fred RoostaUniversity of QueenslandVerified email at uq.edu.au
Siyuan WuPostdoctorate researcher and Lecturer 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
Dimension-independent likelihood-informed MCMC T Cui, KJH Law, YM Marzouk Journal of Computational Physics 304 (1), 109-137, 2016	225	2016
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	211	2015
Likelihood-informed dimension reduction for nonlinear inverse problems T Cui, J Martin, YM Marzouk, A Solonen, A Spantini Inverse Problems 30 (11), 114015, 2014	188	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	161	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	148	2015
Multifidelity importance sampling B Peherstorfer, T Cui, Y Marzouk, K Willcox Computer Methods in Applied Mechanics and Engineering 300, 490-509, 2016	144	2016
A Stein variational Newton method G Detommaso, T Cui, Y Marzouk, A Spantini, R Scheichl Advances in Neural Information Processing Systems 31, 2018	136	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	91	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	69	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	43	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	42*	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	38	2017
Optimization methods for inverse problems N Ye, F Roosta-Khorasani, T Cui 2017 MATRIX Annals, 121-140, 2019	33	2019
Deep composition of tensor-trains using squared inverse rosenblatt transports T Cui, S Dolgov Foundations of Computational Mathematics 22 (6), 1863-1922, 2022	31	2022
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	30	2019
On dimension reduction in Gaussian filters A Solonen, T Cui, J Hakkarainen, Y Marzouk Inverse Problems 32 (4), 045003, 2016	30	2016
Data-free likelihood-informed dimension reduction of Bayesian inverse problems T Cui, O Zahm Inverse Problems 37 (4), 045009, 2021	25	2021
A unified performance analysis of likelihood-informed subspace methods T Cui, XT Tong Bernoulli 28 (4), 2788-2815, 2022	24	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	24	2020
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	22	2023

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