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On the Asymptotical Regularization for Linear Inverse Problems in Presence of White Noise

期刊: SIAM-ASA JOURNAL ON UNCERTAINTY QUANTIFICATION, 2021; 9 (1)

We interpret steady linear statistical inverse problems as artificial dynamic systems with white noise and introduce a stochastic differential equatio......

Lattice Boltzmann Method for Stochastic Convection-Diffusion Equations

期刊: SIAM-ASA JOURNAL ON UNCERTAINTY QUANTIFICATION, 2021; 9 (2)

In this paper, we propose a lattice Boltzmann method (LBM) for stochastic convection-diffusion equations (CDEs). The stochastic Galerkin method is emp......

A Defensive Marginal Particle Filtering Method for Data Assimilation

期刊: SIAM-ASA JOURNAL ON UNCERTAINTY QUANTIFICATION, 2020; 8 (3)

Particle filtering (PF) is an often used method to estimate the states of dynamical systems. A major limitation of the standard PF method is that the ......

Resource-Constrained Model Selection for Uncertainty Propagation and Data Assimilation

期刊: SIAM-ASA JOURNAL ON UNCERTAINTY QUANTIFICATION, 2020; 8 (3)

All observable phenomena can be described by alternative mathematical models, which vary in their fidelity and computational cost. Selection of an app......

Bayesian Optimization of Expected Quadratic Loss for Multiresponse Computer Experiments with internal Noise

期刊: SIAM-ASA JOURNAL ON UNCERTAINTY QUANTIFICATION, 2020; 8 (3)

Design of systems based on computer simulations is prevalent. An important idea to improve design quality, called robust parameter design (RPD), is to......

On the Improved Rates of Convergence for Matern-Type Kernel Ridge Regression with Application to Calibration of Computer Models

期刊: SIAM-ASA JOURNAL ON UNCERTAINTY QUANTIFICATION, 2020; 8 (4)

Kernel ridge regression is an important nonparametric method for estimating smooth functions. We introduce a new set of conditions under which the act......

Bayesian Parameter Identification in Cahn-Hilliard Models for Biological Growth

期刊: SIAM-ASA JOURNAL ON UNCERTAINTY QUANTIFICATION, 2019; 7 (2)

We consider the inverse problem of parameter estimation in a diffuse interface model for tumor growth. The model consists of a fourth-order Cahn-Hilli......

JIF:1.65

On the Instability Issue of Gradient-Enhanced Gaussian Process Emulators for Computer Experiments

期刊: SIAM-ASA JOURNAL ON UNCERTAINTY QUANTIFICATION, 2018; 6 (2)

How to incorporate the gradient information of a computer code is an important problem in computer experiments. The gradient-enhanced Gaussian process......

JIF:1.65

Bayesian Inference via Filtering Equations for Ultrahigh Frequency Data (II): Model Selection

期刊: SIAM-ASA JOURNAL ON UNCERTAINTY QUANTIFICATION, 2018; 6 (1)

For the general partially observed framework of Markov processes with marked point process observations proposed in [G. X. Hu, D. R. Kuipers, and Y. Z......

JIF:1.65

Bayesian Inference via Filtering Equations for Ultrahigh Frequency Data (I): Model and Estimation

期刊: SIAM-ASA JOURNAL ON UNCERTAINTY QUANTIFICATION, 2018; 6 (1)

We propose a general partially observed framework of Markov processes with marked point process observations for ultrahigh frequency (UHF) data. The m......

JIF:1.65

A Hybrid Adaptive MCMC Algorithm in Function Spaces

期刊: SIAM-ASA JOURNAL ON UNCERTAINTY QUANTIFICATION, 2017; 5 (1)

The preconditioned Crank-Nicolson (pCN) method is a Markov Chain Monte Carlo (MCMC) scheme, specifically designed to perform Bayesian inferences in fu......

JIF:1.37

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