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Jinglai Li
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Adaptive construction of surrogates for the Bayesian solution of inverse problems
J Li, YM Marzouk
SIAM Journal on Scientific Computing 36 (3), A1163-A1186, 2014
1372014
An efficient surrogate-based method for computing rare failure probability
J Li, J Li, D Xiu
Journal of Computational Physics 230 (24), 8683-8697, 2011
1332011
Gradual Crossover from Subdiffusion to Normal Diffusion: A Many-Body Effect in Protein Surface Water
P Tan, Y Liang, Q Xu, E Mamontov, J Li, X Xing, L Hong
Physical Review Letters 120 (24), 248101, 2018
782018
Adaptive Gaussian process approximation for Bayesian inference with expensive likelihood functions
H Wang, J Li
Neural computation 30 (11), 3072-3094, 2018
662018
Bayesian inference and uncertainty quantification for medical image reconstruction with Poisson data
Q Zhou, T Yu, X Zhang, J Li
SIAM Journal on Imaging Sciences 13 (1), 29-52, 2020
352020
Gaussian process surrogates for failure detection: a Bayesian experimental design approach
H Wang, G Lin, J Li
Journal of Computational Physics 313, 247-259, 2016
342016
A TV-Gaussian prior for infinite-dimensional Bayesian inverse problems and its numerical implementations
Z Yao, Z Hu, J Li
Inverse Problems 32, 075006:1-19, 2016
322016
An adaptive reduced basis ANOVA method for high-dimensional Bayesian inverse problems
Q Liao, J Li
Journal of Computational Physics 396, 364-380, 2019
302019
Noise-induced perturbations of dispersion-managed solitons
J Li, E Spiller, G Biondini
Physical Review A—Atomic, Molecular, and Optical Physics 75 (5), 053818, 2007
282007
On an adaptive preconditioned Crank-Nicolson MCMC algorithm for infinite dimensional Bayesian inferences
Z Hu, Z Yao, J Li
Journal of Computational Physics 332, 492-503, 2017
252017
Increasing the efficiency of Sequential Monte Carlo samplers through the use of approximately optimal L-kernels
PL Green, LJ Devlin, RE Moore, RJ Jackson, J Li, S Maskell
Mechanical Systems and Signal Processing 162, 108028, 2022
222022
A note on the Karhunen–Loève expansions for infinite-dimensional Bayesian inverse problems
J Li
Statistics & Probability Letters 106, 1-4, 2015
202015
Anisotropic hinge model for polarization-mode dispersion in installed fibers
J Li, G Biondini, WL Kath, H Kogelnik
Optics letters 33 (16), 1924-1926, 2008
182008
Nonlocal TV-Gaussian prior for Bayesian inverse problems with applications to limited CT reconstruction.
D Lv, Q Zhou, JK Choi, J Li, X Zhang
Inverse Problems & Imaging 14 (1), 2020
172020
An approximate empirical Bayesian method for large-scale linear-Gaussian inverse problems
Q Zhou, W Liu, J Li, YM Marzouk
Inverse Problems 34 (9), 2018
152018
An Adaptive Independence Sampler MCMC Algorithm for Bayesian Inferences of Functions
Z Feng, J Li
SIAM Journal on Scientific Computing 40 (3), A1301–A1321, 2018
15*2018
Outage statistics in a waveplate hinge model of polarization-mode dispersion
J Li, G Biondini, WL Kath, H Kogelnik
Journal of Lightwave Technology 28 (13), 1958-1968, 2010
152010
A surrogate accelerated multicanonical Monte Carlo method for uncertainty quantification
K Wu, J Li
Journal of Computational Physics 321, 1098-1109, 2016
142016
NF-ULA: Normalizing Flow-Based Unadjusted Langevin Algorithm for Imaging Inverse Problems
Z Cai, J Tang, S Mukherjee, J Li, CB Schönlieb, X Zhang
SIAM Journal on Imaging Sciences 17 (2), 820-860, 2024
12*2024
Clustered active-subspace based local Gaussian Process emulator for high-dimensional and complex computer models
J Xiong, X Cai, J Li
Journal of Computational Physics 450, 110840, 2022
122022
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