publications

2026

2026

1. EM

   Bernstein approximation and beyond: Proofs by means of elementary probability theory

   Tiangang Cui and Friedrich Pillichshammer

   Elemente der Mathematik. Revue de mathematiques elementaires. Rivista di matematica elementare., 2026

   DOI arXiv
2. MathComp

   Sequential transport maps using SoS density estimation and $\backslashalpha $-divergences

   Benjamin Zanger, Olivier Zahm, Tiangang Cui, and 1 more author

   Mathematics of Computation, 2026

   arXiv
3. JUQ

   Subspace accelerated measure transport methods for fast and scalable sequential experimental design, with application to photoacoustic imaging

   Tiangang Cui, Karina Koval, Roland Herzog, and 1 more author

   SIAM/ASA Journal on Uncertainty Quantification, 2026

   arXiv
4. arxiv

   Low-rank Bayesian matrix completion via geodesic Hamiltonian Monte Carlo on Stiefel manifolds

   Tiangang Cui and Alex Gorodetsky

   Foundation of Data Science, 2026

   arXiv
5. JCAM

   A tensor-train reduced basis solver for parameterized partial differential equations on Cartesian grids

   Nicholas Mueller, Yiran Zhao, Santiago Badia, and 1 more author

   Journal of Computational and Applied Mathematics, 2026

   DOI arXiv

2025

2025

1. AAP

   Convergence speed and approximation accuracy of numerical MCMC

   Tiangang Cui, Jing Dong, Ajay Jasra, and 1 more author

   Advances in Applied Probability, 2025

   DOI arXiv
2. ACM

   Quasi-Monte Carlo methods for mixture distributions and approximated distributions via piecewise linear interpolation: Quasi-Monte Carlo methods for mixture distributions and approximated...

   Tiangang Cui, Josef Dick, and Friedrich Pillichshammer

   Advances in Computational Mathematics, 2025

   DOI arXiv
3. Bernstein approximation and beyond: proofs by means of elementary probability theory

   Tiangang Cui and Friedrich Pillichshammer

   Elemente der Mathematik, 2025

   arXiv
4. InfInf

   Sharp detection of low-dimensional structure in probability measures via dimensional logarithmic Sobolev inequalities

   Matthew TC Li, Tiangang Cui, Fengyi Li, and 2 more authors

   Information and Inference: A Journal of the IMA, 2025

   DOI arXiv

2024

2024

1. SISC

   Deep importance sampling using tensor-trains with application to a priori and a posteriori rare event estimation

   Tiangang Cui, Sergey Dolgov, and Robert Scheichl

   SIAM Journal on Scientific Computing, 2024

   DOI arXiv
2. IP

   Multilevel dimension-independent likelihood-informed MCMC for large-scale inverse problems

   Tiangang Cui, Gianluca Detommaso, and Robert Scheichl

   Inverse Problems, 2024

   DOI arXiv
3. JMLR

   Tensor-train methods for sequential state and parameter learning in state-space models

   Yiran Zhao and Tiangang Cui

   Journal of Machine Learning Research, 2024

   arXiv
4. JSC

   Multilevel Monte Carlo Methods for Stochastic Convection–Diffusion Eigenvalue Problems

   Tiangang Cui, Hans De Sterck, Alexander D Gilbert, and 2 more authors

   Journal of Scientific Computing, 2024

   DOI arXiv

2023

2023

1. CiCP

   A variational neural network approach for glacier modelling with nonlinear rheology

   Tiangang Cui, Zhongjian Wang, and Zhiwen Zhang

   Communications in Computational Physics, 2023

   DOI arXiv
2. JCP

   Scalable conditional deep inverse Rosenblatt transports using tensor trains and gradient-based dimension reduction

   Tiangang Cui, Sergey Dolgov, and Olivier Zahm

   Journal of Computational Physics, 2023

   DOI arXiv

2022

2022

1. Bernoulli

   A unified performance analysis of likelihood-informed subspace methods

   Tiangang Cui and Xin T Tong

   Bernoulli, 2022

   DOI arXiv
2. MathComp

   Certified dimension reduction in nonlinear Bayesian inverse problems

   Olivier Zahm, Tiangang Cui, Kody Law, and 2 more authors

   Mathematics of Computation, 2022

   DOI arXiv
3. IP

   Prior normalization for certified likelihood-informed subspace detection of Bayesian inverse problems

   Tiangang Cui, Xin T Tong, and Olivier Zahm

   Inverse Problems, 2022

   DOI arXiv
4. FoCM

   Deep composition of tensor trains using squared inverse Rosenblatt transports

   Tiangang Cui and Sergey Dolgov

   Foundations of Computational Mathematics, 2022

   DOI arXiv

2021

2021

1. IP

   Data-free likelihood-informed dimension reduction of Bayesian inverse problems

   Tiangang Cui and Olivier Zahm

   Inverse Problems, 2021

   DOI arXiv
2. JUQ

   Optimization-based Markov chain Monte Carlo methods for nonlinear hierarchical statistical inverse problems

   Johnathan M Bardsley and Tiangang Cui

   SIAM/ASA Journal on Uncertainty Quantification, 2021

   DOI arXiv
3. NeuroImage

   Identification of community structure-based brain states and transitions using functional MRI

   Lingbin Bian, Tiangang Cui, BT Thomas Yeo, and 3 more authors

   NeuroImage, 2021

   DOI arXiv

2020

2020

1. IP

   Semivariogram methods for modeling Whittle–Matérn priors in Bayesian inverse problems

   Richard D Brown, Johnathan M Bardsley, and Tiangang Cui

   Inverse Problems, 2020

   DOI arXiv
2. SISC

   Scalable optimization-based sampling on function space

   Johnathan M Bardsley, Tiangang Cui, Youssef M Marzouk, and 1 more author

   SIAM Journal on Scientific Computing, 2020

   DOI arXiv
3. PeerJ

   A non-linear reverse-engineering method for inferring genetic regulatory networks

   Siyuan Wu, Tiangang Cui, Xinan Zhang, and 1 more author

   PeerJ, 2020
4. GEM

   Randomized reduced forward models for efficient Metropolis–Hastings MCMC, with application to subsurface fluid flow and capacitance tomography

   Colin Fox, Tiangang Cui, and Markus Neumayer

   GEM-International Journal on Geomathematics, 2020

   DOI arXiv

2019

2019

1. IJNME

   A posteriori stochastic correction of reduced models in delayed-acceptance MCMC, with application to multiphase subsurface inverse problems

   Tiangang Cui, Colin Fox, and Michael J O’Sullivan

   International Journal for Numerical Methods in Engineering, 2019

   DOI arXiv
2. IJUQ

   Using parallel Markov chain Monte Carlo to quantify uncertainties in geothermal reservoir calibration

   Tiangang Cui, Colin Fox, Mike O’Sullivan, and 1 more author

   International Journal for Uncertainty Quantification, 2019

   DOI
3. J. Struct. Geol.

   Extraction of high-resolution structural orientations from digital data: A Bayesian approach

   Samuel T Thiele, Lachlan Grose, Tiangang Cui, and 2 more authors

   Journal of Structural Geology, 2019

   DOI

2018

2018

1. J. Struct. Biol

   Rapid near-atomic resolution single-particle 3D reconstruction with SIMPLE

   Cyril F Reboul, Simon Kiesewetter, Michael Eager, and 5 more authors

   Journal of structural biology, 2018

   DOI

2017

2017

1. SISC

   Goal-oriented optimal approximations of Bayesian linear inverse problems

   Alessio Spantini, Tiangang Cui, Karen Willcox, and 2 more authors

   SIAM Journal on Scientific Computing, 2017

   DOI arXiv
2. SISC

   Bayesian inverse problems with l_1 priors: a randomize-then-optimize approach

   Zheng Wang, Johnathan M Bardsley, Antti Solonen, and 2 more authors

   SIAM Journal on Scientific Computing, 2017

   DOI arXiv

2016

2016

1. JCP

   Dimension-independent likelihood-informed MCMC

   Tiangang Cui, Kody JH Law, and Youssef M Marzouk

   Journal of Computational Physics, 2016

   DOI arXiv
2. JHE

   Pragmatic approach to calibrating distributed parameter groundwater models from pumping test data using adaptive delayed acceptance MCMC

   Tiangang Cui, Nicholas Dudley Ward, Simon Eveson, and 1 more author

   Journal of Hydrologic Engineering, 2016
3. IP

   On dimension reduction in Gaussian filters

   Antti Solonen, Tiangang Cui, Janne Hakkarainen, and 1 more author

   Inverse Problems, 2016

   DOI arXiv
4. JCP

   Scalable posterior approximations for large-scale Bayesian inverse problems via likelihood-informed parameter and state reduction

   Tiangang Cui, Youssef M Marzouk, and Karen E Willcox

   Journal of Computational Physics, 2016

   DOI arXiv
5. CMAME

   Multifidelity importance sampling

   Benjamin Peherstorfer, Tiangang Cui, Youssef Marzouk, and 1 more author

   Computer Methods in Applied Mechanics and Engineering, 2016

   DOI

2015

2015

1. SISC

   Optimal low-rank approximations of Bayesian linear inverse problems

   Alessio Spantini, Antti Solonen, Tiangang Cui, and 3 more authors

   SIAM Journal on Scientific Computing, 2015

   DOI arXiv
2. IJNME

   Data-driven model reduction for the Bayesian solution of inverse problems

   Tiangang Cui, Youssef M Marzouk, and Karen E Willcox

   International Journal for Numerical Methods in Engineering, 2015

   DOI arXiv

2014

2014

1. JHE

   Characterization of parameters for a spatially heterogenous aquifer from pumping test data

   Tiangang Cui, Nicholas Dudley Ward, and Jari Kaipio

   Journal of Hydrologic Engineering, 2014
2. IP

   Likelihood-informed dimension reduction for nonlinear inverse problems

   Tiangang Cui, James Martin, Youssef M Marzouk, and 2 more authors

   Inverse Problems, 2014

   DOI arXiv

2013

2013

1. JHE

   Uncertainty quantification for stream depletion tests

   Tiangang Cui and Nicholas Dudley Ward

   Journal of Hydrologic Engineering, 2013

2011

2011

1. WRR

   Bayesian calibration of a large-scale geothermal reservoir model by a new adaptive delayed acceptance Metropolis Hastings algorithm

   T Cui, C Fox, and MJ O’sullivan

   Water Resources Research, 2011

   DOI

2019

2019

1. Optimization methods for inverse problems

   Nan Ye, Farbod Roosta-Khorasani, and Tiangang Cui

   In 2017 MATRIX Annals, 2019

   DOI
2. A Metropolis-Hastings-within-Gibbs sampler for nonlinear hierarchical-Bayesian inverse problems

   Johnathan M Bardsley and Tiangang Cui

   In 2017 MATRIX Annals, 2019

   DOI

2018

2018

1. NIPS

   A Stein variational Newton method

   Gianluca Detommaso, Tiangang Cui, Youssef Marzouk, and 2 more authors

   In Advances in Neural Information Processing Systems, 2018

   arXiv
2. IEEE

   Mathematical modelling of genetic network for regulating the fate determination of hematopoietic stem cells

   Siyuan Wu, Tiangang Cui, and Tianhai Tian

   In 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2018
3. MCQMC

   Network Structure Change Point Detection by Posterior Predictive Discrepancy

   Lingbin Bian, Tiangang Cui, Georgy Sofronov, and 1 more author

   In International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing, 2018

2026

1. arxiv

   FLUID: Flow-based Unified Inference for Dynamics

   Tiangang Cui, Xiaodong Feng, Chenlong Pei, and 2 more authors

   2026

   arXiv
2. arxiv

   Multiscale Structural Reliability Analysis in high dimensions with Tensor Trains and Physics-Augmented Neural Networks

   Aryan Tyagi, Alex Beer, Tiangang Cui, and 1 more author

   2026

   arXiv

2025

1. arxiv

   Second order interlaced polynomial lattice rules for integration over $\backslashmathbb {R}\^ s$

   Tiangang Cui, Josef Dick, and Friedrich Pillichshammer

   2025

   arXiv

2024

1. arxiv

   Optimal Riemannian metric for Poincar {\backslash’e} inequalities and how to ideally precondition Langevin dymanics

   Tiangang Cui, Xin Tong, and Olivier Zahm

   2024

   arXiv
2. arxiv

   Stein’s method for marginals on large graphical models

   Tiangang Cui, Shuigen Liu, and Xin T Tong

   2024

   arXiv

2023

1. arxiv

   Self-reinforced polynomial approximation methods for concentrated probability densities

   Tiangang Cui, Sergey Dolgov, and Olivier Zahm

   2023

   arXiv

2019

1. arxiv

   Stein variational online changepoint detection with applications to Hawkes processes and neural networks

   Gianluca Detommaso, Hanne Hoitzing, Tiangang Cui, and 1 more author

   2019

   arXiv