Articles with public access mandates - Shuai LuLearn more
Not available anywhere: 14
A recursive algorithm for multifrequency acoustic inverse source problems
G Bao, S Lu, W Rundell, B Xu
SIAM Journal on Numerical Analysis 53 (3), 1608-1628, 2015
Mandates: National Natural Science Foundation of China
Model functions in the modified L-curve method—case study: the heat flux reconstruction in pool boiling
Y Heng, S Lu, A Mhamdi, SV Pereverzev
Inverse Problems 26 (5), 055006, 2010
Mandates: Austrian Science Fund, German Research Foundation
A model function method in regularized total least squares
S Lu, SV Pereverzev, U Tautenhahn
Applicable Analysis 89 (11), 1693-1703, 2010
Mandates: Austrian Science Fund
Stochastic gradient descent for linear inverse problems in Hilbert spaces
S Lu, P Mathé
Mathematics of Computation 91 (336), 1763-1788, 2022
Mandates: National Natural Science Foundation of China
Sparse recovery by the standard Tikhonov method
S Lu, SV Pereverzev
Numerische Mathematik 112 (3), 403-424, 2009
Mandates: Austrian Science Fund
A novel formulation and sequential solution strategy with time-space adaptive mesh refinement for efficient reconstruction of local boundary heat flux
J Luo, QQ Yang, S Lu, A Mhamdi, DC Mo, SS Lyu, Y Heng
International Journal of Heat and Mass Transfer 141, 1288-1300, 2019
Mandates: National Natural Science Foundation of China
3-D ionospheric tomography using model function in the modified L-curve method
S Wang, S Huang, S Lu, B Yan
IEEE Transactions on Geoscience and Remote Sensing 57 (6), 3135-3147, 2018
Mandates: National Natural Science Foundation of China
LINEARIZED INVERSE SCHRÖDINGER POTENTIAL PROBLEM WITH PARTIAL DATA AND ITS DEEP NEURAL NETWORK INVERSION.
S Zou, S Lu, B Xu
Inverse Problems & Imaging 16 (6), 2022
Mandates: National Natural Science Foundation of China
Identification of the exchange coefficient from indirect data for a coupled continuum pipe-flow model
X Wu, P Kügler, S Lu
Chinese Annals of Mathematics, Series B 35 (3), 483-500, 2014
Mandates: National Natural Science Foundation of China
Multiscale support vector regression method in Sobolev spaces on bounded domains
B Xu, S Lu, M Zhong
Applicable Analysis 94 (3), 548-569, 2015
Mandates: National Natural Science Foundation of China
Randomized matrix approximation to enhance regularized projection schemes in inverse problems
S Lu, P Mathé, SV Pereverzev
Inverse Problems 36 (8), 085013, 2020
Mandates: National Natural Science Foundation of China
Multiscale support vector approach for solving ill-posed problems
M Zhong, YC Hon, S Lu
Journal of Scientific Computing 64 (2), 317-340, 2015
Mandates: National Natural Science Foundation of China
On the inverse source problem with boundary data at many wave numbers
V Isakov, S Lu
Inverse Problems and Related Topics: Shanghai, China, October 12–14, 2018, 59-80, 2020
Mandates: US National Science Foundation, National Natural Science Foundation of China
Relaxing Alternating Direction Method of Multipliers (ADMM) for Linear Inverse Problems
Z Wu, S Lu
New Trends in Parameter Identification for Mathematical Models, 317-345, 2018
Mandates: National Natural Science Foundation of China
Available somewhere: 30
Increasing stability in the inverse source problem with many frequencies
J Cheng, V Isakov, S Lu
Journal of Differential Equations 260 (5), 4786-4804, 2016
Mandates: US National Science Foundation, National Natural Science Foundation of China
Multi-parameter regularization and its numerical realization
S Lu, SV Pereverzev
Numerische Mathematik 118, 1-31, 2011
Mandates: Austrian Science Fund
Balancing principle in supervised learning for a general regularization scheme
S Lu, P Mathé, SV Pereverzev
Applied and Computational Harmonic Analysis 48 (1), 123-148, 2020
Mandates: Austrian Science Fund, National Natural Science Foundation of China
On the generalized discrepancy principle for Tikhonov regularization in Hilbert scales
S Lu, SV Pereverzev, Y Shao, U Tautenhahn
The Journal of Integral Equations and Applications, 483-517, 2010
Mandates: Austrian Science Fund
Regularized total least squares: computational aspects and error bounds
S Lu, SV Pereverzev, U Tautenhahn
SIAM journal on matrix analysis and applications 31 (3), 918-941, 2010
Mandates: Austrian Science Fund
Discrepancy curves for multi-parameter regularization
S Lu, SV Pereverzev, Y Shao, U Tautenhahn
Walter de Gruyter GmbH & Co. KG 18 (6), 655-676, 2010
Mandates: Austrian Science Fund
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