Tiangang Cui

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MONASH UNIVERSITY

Australia

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Enabling three dimensional stochastic geological modelling

Open Date: 2018-01-01

Close Date: 2020-12-31

Articles (15)

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2025

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2022

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2022

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2021

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2020

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2020

Collaborators (6)

Robert Scheichl

Heidelberg University

GERMANY

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Friedrich Pillichshammer

A.Univ.-Prof.

Johannes Kepler University Linz

AUSTRIA

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Colin Fox

University of Otago

NEW ZEALAND

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Xin Tong

Assistant professor

National University of Singapore (NUS)

SINGAPORE

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Sergey Dolgov

University of Bath

UNITED KINGDOM

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Josef Dick

Professor

University of New South Wales

AUSTRALIA

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Tiangang Cui

Research Interests

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Contact this professor

Recent Grants

Articles (15)

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

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

Deep Importance Sampling Using Tensor Trains with Application to a Priori and a Posteriori Rare Events

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

Multilevel Monte Carlo Methods for Stochastic Convection–Diffusion Eigenvalue Problems

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

Deep Composition of Tensor-Trains Using Squared Inverse Rosenblatt Transports

CERTIFIED DIMENSION REDUCTION IN NONLINEAR BAYESIAN INVERSE PROBLEMS

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

A unified performance analysis of likelihood-informed subspace methods

Optimization-Based Markov Chain Monte Carlo Methods for Nonlinear Hierarchical Statistical Inverse Problems

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

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

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

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

Collaborators (6)

Robert Scheichl

Friedrich Pillichshammer

Colin Fox

Xin Tong

Sergey Dolgov

Josef Dick

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