The most updated publication list is available from Google
Scholar page.
Monographs:
1.
Kazufumi Ito, Bangti Jin.
Inverse Problems: Tikhonov Theory and Algorithms, World Publishing, 2014. publisher,
Amazon
2.
Bangti Jin. Fractional Differential Equations.
(Applied Mathematical Sciences, vol. 206). Springer 2021. publisher, Amazon
3.
Bangti Jin, Zhi Zhou. Numerical Treatment and Analysis
of Time-Fractional Evolution Equations (Applied Mathematical Sciences, vol.
214). Springer 2023. publisher
Journal articles:
2025
1. Kuang
Huang, Bangti Jin, Zhi Zhou. On an inverse problem of
the generalized bathtub model for network trip flows. SIAM Journal on Applied
Mathematics, in press.
2. Kuang
Huang, Bangti Jin, Yavar Kian, George Sadaka, Zhi Zhou. Point source
identification for subdiffusion from a posteriori
internal measurement. SIAM Journal on Applied Mathematics, in press.
3. Bangti
Jin, Fengru Wang, Yifeng
Xu. Adaptive finite element approximations of conductivity inclusions in a semilinear elliptic problem related to cardiac
electrophysiology. IMA Journal of Numerical Analysis, in press.
4. Kazufumi Ito, Bangti Jin, Fengru
Wang, Jun Zou. An iterative direct sampling method for elliptic inverse
problems with limited Cauchy data. SIAM Journal on Imaging Sciences, in press.
5. Tianhao Hu, Bangti Jin, Fengru
Wang. An iterative deep Ritz method for monotone elliptic problems. Journal of
Computational Physics, 2025;527: 113791.
6. Riccardo
Barbano, Alexander Adenker, Hyungjin
Ching, Tae Hoon Roh, Simon Arrdige, Peter Maass,
Bangti Jin, Jong Chul Ye. Steerable conditional diffusion for
out-of-distribution adaptation in imaging inverse problems. IEEE Transactions
on Medical Imaging 2025, in press.
(10.1109/TMI.2024.3524797)
7. Siyu
Cen, Bangti Jin, Xiyao Li, Zhi Zhou. Imaging
anisotropic conductivity from internal measurements with mixed least-squares
deep neural networks. Journal of Computational Physics 2025; 523, 113648, 25
pp.
8. Jiho
Hong, Bangti Jin, Yavar Kian. Identification of a spatially-dependent
variable order in one-dimensional subdiffusion. SIAM
Journal on Mathematical Analysis 2025;57(2): 1315--1341.
9. Xinling Liu, Jianjun Wang, Bangti Jin. Theory and
fast learned solver for l1-TV regularization. Inverse Problems 2025; 41(1),
015001, 31 pp.
10. Bangti
Jin, Qingle Lin, Zhi Zhou. Optimizing coarse
propagators in parareal algorithms. SIAM Journal on
Scientific Computing 2025; 47(2): A735-A761.
2024
1. Tim
Jahn, Bangti Jin. Early stopping of untrained convolutional neural networks.
SIAM Journal on Imaging Sciences 2024; 17(4): 2331-2361.
2. Junqing Chen, Bangti Jin, Haibo
Liu. Solving inverse obstacle scattering problem with latent surface
representation. Inverse Problems 2024;40(6), 065013, 30 pp.
3. Tianhao Hu, Bangti Jin, Zhi Zhou. Solving Poisson
problems in polygonal domains with singularity enriched physics informed neural
networks. SIAM Journal on Scientific Computing 2024; 46 (4): C369--C398.
4. Bangti
Jin, Jing Li, Yifeng Xu, Shengfeng
Zhu. An adaptive phase-field method for structural topology optimization.
Journal of Computational Physics 2024; 506: 112932, 27 pp.
5. Bangti
Jin, Zehui Zhou, Jun Zou. On the approximation of
bi-Lipschitz maps via invertible neural networks. Neural Networks 2024; 174,
106214, 19 pp.
6. Riccardo
Barbano, Javier Antoran, Johannes Leuschner, Jose
Miguel Hernandez-Lobato, Zeljko Kereta, Bangti Jin. Image reconstruction in
deep image prior subspaces. Transactions of Machine Learning Research 2024. https://openreview.net/forum?id=torWsEui9N
7. Imraj Singh, Alexander Denker, Riccardo Barbano,
Zeljko Kereta, Bangti Jin, Kris Thielemans, Peter Maass, Simon Arridge. Score-based generative models for PET image
reconstruction. Journal of Machine Learning for Biomedical Imaging 2024:001
vol. 2, pp. 547--585.
8. Bangti
Jin, Kwancheol Shin, Zhi Zhou. Numerical recovery of
a time-dependent potential in subdiffusion. Inverse
Problems 2024; 40(2): 025008, 34 pp.
9. Bangti
Jin, Xiyao Li, Qimeng Quan,
Zhi Zhou. Conductivity imaging from internal measurements using mixed
least-squared deep neural networks. SIAM Journal on Imaging Sciences 2024;
17(1): 147--187.
2023
1. Riccardo
Barbano, Javier Antoran, Johannes Leuschner, Jose
Miguel Hernandez-Lobato, Bangti Jin. Uncertainty estimation for computed
tomography with a linearised deep image prior,
Transactions of Machine Learning Research, 2023.
2. Siyu
Cen, Bangti Jin, Kwancheol Shin, Zhi Zhou. Electrical impedance
tomography with deep Calder\'{o}n method. Journal of
Computational Physics 2023; 493, 112427, 14 pp.
3. Siyu
Cen, Bangti Jin, Qimeng Quan, Zhi Zhou. Hybrid
neural-network FEM approximation of diffusion coefficient in elliptic and
parabolic problems. IMA Journal on Numerical Analysis 2024; 44(5): 3059--3093.
4. Siyu
Cen, Bangti Jin, Yikan Liu, Zhi Zhou. Numerical
recovery of multiple parameters in subdiffusion from
one lateral boundary measurement. Inverse Problems 2023; 39(10): 104001, 31 pp.
5. Tianhao Hu, Bangti Jin, Zhi Zhou. Solving
elliptic problems with singular sources using singularity splitting deep Ritz
method. SIAM Journal on Scientific Computing 2023; 45(4): A2043--A2074.
6. Bangti
Jin, Yavar Kian, Zhi Zhou. Inverse problems for subdiffusion
from observation at an unknown terminal time. SIAM Journal on Applied
Mathematics 2023; 83 (4): 1496-1517.
7. Bangti
Jin, Zeljko Kereta. On the convergence of stochastic gradient descent for
linear inverse problems in Banach spaces. SIAM Journal on Imaging Sciences
2023; 16 (2): 671-705.
8. Bangti
Jin, Yavar Kian. Recovery of the support of distributed order fractional
diffusion in an unknown medium. Communications in Mathematical Sciences 2023;
21(7):1791--1813.
9. Riccardo
Barbano, Johannes Leuschner, Maximilian Schmidt, Alexander Denker, Andreas
Hauptmann, Peter Maass, Bangti Jin. An educated warm start for deep image
prior-based micro-CT reconstruction. IEEE Transactions on Computational
Imaging, in press.
10. Bangti
Jin, Zhi Zhou. Recovery of a space-time dependent diffusion coefficient in subdiffusion: stability, approximation and error analysis.
IMA Journal of Numerical Analysis 2023; 43 (4): 2496--2531.
11. Bangti
Jin, Xiliang Lu, Qimeng
Quan, Zhi Zhou. Convergence rate analysis of Galerkin
approximations of inverse potential problem. Inverse Problems 2023; 39(1): 015008, 26 pp.
12. Robert
Twyman, Simon Arridge, Zeljko Kereta, Bangti Jin,
Ludovica Brusaferri, Sangtae
Ahn, Charles Stearns, Brian F. Hutton, Irene A. Burger, Fotis Kotasidis, Kris Thielemans. An investigation of stochastic
variance reduction algorithms for 3D penalised PET
image reconstruction. IEEE Transactions on Medical Imaging 2023; 42(1): 29--41.
2022
1. Riccardo
Barbano, Zeljko Kereta, Andreas Hauptman, Simon Arridge,
Bangti Jin. Unsupervised knowledge transfer for learned image reconstruction.
Inverse Problems 2022; 38(10), 104004, 28 pp.
2. Riccardo
Barbano, Johannes Leuschner,
Maximilian Schmidt, Alexander Denker, Andreas Hauptmann, Peter
Maass, Bangti Jin. An educated warm start for deep image prior-based micro CT reconstruction. IEEE Transactions on Computational
Imaging 2022; 8: 1210--1222.
3. Bangti
Jin, Xiyao Li, Xiliang Lu.
Imaging conductivity from current density magnitude using neural networks.
Inverse Problems 2022; 38(7): 075003, 36 pp.
4. Huan
Liu, Bangti Jin, Xiliang Lu. Imaging anisotropic
conductivities from current densities. SIAM Journal on Imaging Sciences
2022;15(2): 860--891.
5. Bangti
Jin, Zehui Zhou, Jun Zou. An analysis of stochastic
variance reduced gradient for linear inverse problems. Inverse Problems 2022;
38(2): 025009, 34 pp.
6. Bangti
Jin, Yavar Kian. Recovery of the order of derivation in time-fractional
differential equations in an unknown medium. SIAM Journal on Applied
Mathematics 2022;82(3): 1045--1067.
2021
1. Chen
Zhang, Riccardo Barbano, Bangti Jin. Conditional variational autoencoder for
image reconstruction. Computation 2021; 9(11): 114.
2. Zeljko
Kereta, Robert Twyman, Simon Arridge, Kris
Thielemans, Bangti Jin. Stochastic EM methods with variance reduction for penalised PET reconstruction. Inverse Problems 2021;
37(11): 115006, 21 pp.
3. Bangti
Jin, Zhi Zhou. Recovering the potential and order in one-dimensional
time-fractional diffusion with unknown initial condition and source. Inverse
Problems 2021; 37(10): 105009 (28 pp).
4. Bangti
Jin, Yavar Kian. Recovering multiple orders of derivation in time-fractional
differential equations. Proceedings of the Royal Society A 2021; 477(2253):
0210468 (21 pp).
5. Bangti
Jin, Zehui Zhou, Jun Zou. On the saturation
phenomenon of stochastic gradient descent for linear inverse problems, SIAM/ASA
Journal on Uncertainty Quantification 2021; 9(4): 1553--1588.
6. Bangti
Jin, Yavar Kian, Zhi Zhou. Reconstruction of a space-time dependent source in subdiffusion models via a perturbation approach. SIAM
Journal on Mathematical Analysis 2021; 53(4): 4445--4473.
7. Bangti
Jin, Zhi Zhou. Numerical estimation of a diffusion coefficient in subdiffusion equations. SIAM Journal on Control and
Optimization 2021;59(2): 1466--1496.
8. Bangti
Jin, Zhi Zhou. Error analysis of finite element approximations of diffusion
coefficient identification for elliptic and parabolic problems. SIAM Journal on
Numerical Analysis 2021; 59(1): 119--142.
9. Bangti
Jin, Zhi Zhou. An inverse potential problem with subdiffusion:
stability and reconstruction. Inverse Problems 2021;(1): 37, 015006, 26 pp.
10. Jian
Huang, Yuling Jiao, Bangti Jin, Xiliang Lu, Can Yang.
A unified primal dual active set algorithm for nonconvex sparse recovery.
Statistical Sciences 2021; 36(2): 215--238.
2020
1. Bangti Jin,
Tobias Kluth. L1 data fitting for robust reconstruction in magnetic particle
imaging: quantitative evaluation on Open MPI Dataset. International Journal of
Magnetic Particle Imaging 2020;6(2), Article ID: 2012001, DOI:
10.18416/IJMPI.2020.2012001.
2. Tim
Jahn, Bangti Jin. On the discrepancy principle for stochastic gradient descent.
Inverse Problems 2020;36(9): 095009, 30 pp.
3. Bangti
Jin, Zhi Zhou. Incomplete iterative scheme for subdiffusion.
Numerische Mathematik
2020;145(3): 693--725.
4. Bangti
Jin, Buyang Li, Zhi Zhou. Second-order time-stepping
scheme for subdiffusion with a time-dependent
coefficient. Numerische Mathematik
2020; 145(4): 883--913.
5. Manh
Hong Duong, Bangti Jin. Wasserstein gradient flow formulation of the
time-fractional Fokker-Planck equation. Communications in Mathematical Sciences
2020; 18(7): 1949--1975.
6. Bangti
Jin, Zehui Zhou, Jun Zou. On the convergence of
stochastic gradient descent for nonlinear inverse problems. SIAM Journal on
Optimization 2020; 30(2): 1421--1450.
7. Federico
Benvenuto, Bangti Jin. A regularization parameter for Tikhonov regularization
based on predictive risk. Inverse Problems 2020; 36(6), 065004, 24 pp.
8. Bangti
Jin, Yifeng Xu. Adaptive reconstruction for
electrical impedance tomography with a piecewise constant conductivity. Inverse
Problems 2020; 36(1): 014003, 28 pp.
2019
1. Chen
Zhang, Simon Arridge, Bangti Jin. Expectation
propagation for Poisson data. Inverse Problems 2019;35(8), 085006, 27 pp.
2. Bangti
Jin, Buyang Li, Zhi Zhou. Pointwise-in-time error
estimate for an optimal control problem with subdiffusion
constraint. IMA Journal on Numerical Analysis 2020; 40(1): 377--404.
3. Tobias
Kluth, Bangti Jin. Enhanced reconstruction in magnetic particle imaging by
whitening and randomized SVD approximation. Physics in Medicines \& Biology
2019; 64(12): 125026, 21 pp.
4. Bangti
Jin, Yubin Yan, Zhi Zhou. Numerical approximation of stochastic time-fractional
diffusion. ESAIM: Mathematical Modeling and Numerical Analysis 2019; 53(4):
1245--1268.
5. Bangti
Jin, Raytcho Lazarov, Zhi Zhou. Numerical methods for
time-fractional diffusion with nonsmooth data: a
concise overview. Computer Methods in Applied Mechanics and Engineering 2019;
346: 332--358.
6. Bangti
Jin, Buyang Li, Zhi Zhou. Subdiffusion
with a time-dependent coefficient: analysis and numerical solution. Mathematics
of Computation 2019;88(319): 2157--2186.
7. Habib
Ammari, Bangti Jin, Wenlong Zhang. Linearized
reconstruction for diffuse optical spectroscopic imaging. Proceedings of the
Royal Society A, Mathematical, Physical and Engineering Sciences 2019;
475(2221): 20180592, 21 pp.
8. James Adesokan, Bj\"{o}rn Jensen, Bangti Jin, Kim Knudsen. Acousto-electric
tomography with total variation regularization. Inverse Problems 2019;35(3),
035008, 25 pp.
9. Bangti
Jin, Xiliang Lu. On the regularizing property of
stochastic gradient descent. Inverse Problems 2019; 35(1): 015004, 27 pp.
10. Eric T.
Chung, Yalchin Efendiev,
Bangti Jin, Wing Tat Leung, Maria Vasilyeva. Generalized multiscale inversion
for heterogeneous problems. Communication in Computational Physics 2019;25(4):
1177--1212.
2018
1. Tobias
Kluth, Bangti Jin, Guanglian Li. On the degree of
ill-posedness of multi-dimensional magnetic particle
imaging. Inverse Problems 2018; 34(9): 095006, 26 pp.
2. Simon Arridge, Kazufumi Ito, Bangti Jin,
Chen Zhang. Variational Gaussian approximation for Poisson data. Inverse
Problems 2018; 34(2): 025005, 29pp.
3. Beiping
Duan, Bangti Jin, Raytcho Lazarov, Joseph Pasciak,
Zhi Zhou. Space-time Petrov-Galerkin FEM for
fractional parabolic problems. Computational Methods in Applied Mathematics
2018; 18(1): 1--20.
4. Bangti
Jin, Buyang Li, Zhi Zhou. Discrete maximal regularity
of time stepping schemes for fractional evolution equations. Numerische Mathematik 2018; 138
(1): 101--131.
5. Bangti
Jin, Buyang Li, Zhi Zhou. Numerical analysis of
nonlinear subdiffusion equations. SIAM Journal on
Numerical Analysis 2018; 56(1): 1--23.
6. Bangti
Jin, Buyang Li, Zhi Zhou. An analysis of
Crank-Nicolson method for subdiffusion. IMA Journal
of Numerical Analysis 2018; 38(1): 518--541.
2017
1. Bangti
Jin, Buyang Li, Zhi Zhou. On high-order BDF
convolution quadrature for fractional evolution equations. SIAM Journal on
Scientific Computing 2017; 39(6): A3129--A3152.
2. Yuling
Jiao, Bangti Jin, Xiliang Lu. Group sparse recovery
via $\ell^0(\ell^2)$ penalty: theory and algorithm.
IEEE Transactions on Signal Processing, 2017; 65(4): 998--1012.
3. Yuling
Jiao, Bangti Jin, Xiliang Lu. Preasymptotic
convergence of the randomized Kaczmarz method.
Inverse Problems 2017; 33(12), 125012, 21pp.
4. Yuling
Jiao, Bangti Jin, Xiliang Lu. Iterative soft/hard
thresholding homotopy algorithm for sparse recovery.
IEEE Signal Processing Letters 2017;24(6):784--788.
5. Bangti
Jin, Yifeng Xu, Jun Zou. An adaptive finite element
method for electrical impedance tomography. IMA Journal of Numerical Analysis
2017;37(3): 1520--1550.
6. Bangti
Jin, Raytcho Lazarov, Vidar Thomee,
Zhi Zhou. On nonnegativity preservation in finite element methods for subdiffusion equations. Mathematics of Computation,
2017;86(307): 2239--2260.
7. Bangti
Jin, Zhi Zhou. An analysis of the Galerkin proper
orthogonal decomposition for subdiffusion. ESAIM:
Mathematical Modeling and Numerical Analysis 2017; 51(1): 89--113.
2016
1. Bangti
Jin, Raytcho Lazarov, Zhi Zhou. A Petrov-Galerkin finite element method for fractional convection
diffusion equation. SIAM Journal on Numerical Analysis 2016;54(1):481--503.
2. Bangti
Jin, Raytcho Lazarov, Zhi Zhou. Two fully discrete
schemes for fractional diffusion and diffusion wave equations. SIAM Journal on
Scientific Computing; 2016;38(1), A146--A170.
3. Giovanni
Alberti, Habib Ammari, Bangti Jin, Jinkeun Seo, Wenlong Zhang. The linear inverse problem in multifrequency
electrical impedance tomography. SIAM Journal on Imaging Science 2016;9(4):
1525--1551.
4. Bangti
Jin, Raytcho Lazarov, Dongwoo
Sheen, Zhi Zhou. Error estimates for the approximations of distributed-order
time fractional diffusion with nonsmooth data.
Fractional Calculus and Applied Analysis 2016; 19(1): 69--93.
5. Bangti
Jin, Tomoya Takeuchi. Lagrangian optimality system
for a class of nonsmooth convex optimization
problems. Optimization 2016; 65(6): 1151--1166.
6. Kazufumi Ito, Bangti Jin, Tomoya Takeuchi. On a
Legendre tau method for boundary value problems with a Caputo derivative.
Fractional Calculus and Applied Analysis 2016;19(2): 357--378.
7. Bangti
Jin, Raytcho Lazarov, Xiliang
Lu, Zhi Zhou. A simple finite element method for the boundary value problem
with a Riemann-Liouville derivative. Journal of Computational and Applied
Mathematics 2016; 293: 94--111.
8. Bangti
Jin, Raytcho Lazarov, Zhi Zhou. An analysis of the L1
scheme for the subdiffusion equation with nonsmooth data. IMA Journal of Numerical Analysis
2016;36(1): 197--221.
2015
1. Nilabja Guha, Xiaoqing Wu, Yalchin
Efendiev, Bangti Jin, Bani K. Mallick. A Bayesian
variational approach for inverse problems with skew-t error distributions.
Journal of Computational Physics 2015; 301: 377--393.
2. Kazufumi Ito, Bangti Jin, Tomoya Takeuchi. On the
sectorial property of the Caputo derivative. Applied Mathematics Letters 2015;
47: 43--46.
3. Bangti
Jin, Zhi Zhou. A singularity reconstructed finite element method for fractional
boundary value problems. ESAIM Mathematical Modeling and Numerical Analysis
2015; 49(5): 1261--1283.
4. Emilia Bazhlekova, Bangti Jin, Raytcho
Lazarov, Zhi Zhou. An analysis of the Rayleigh-Stokes problem for the
generalized second grade fluid. Numerische Mathematik 2015;131(1): 1--31.
5. Yuling
Jiao, Bangti Jin, Xiliang Lu. A primal-dual active
set with continuation algorithm for the $\ell^0$-regularized optimization
problem. Applied and Computational Harmonic Analysis 2015;39(3): 259--286.
6. Bangti
Jin, Raytcho Lazarov, Joseph Pasciak, William
Rundell. Variational formulation of problems involving fractional order
differential operators. Mathematics of Computation 2015;84(296): 2665--2700.
7. Bangti
Jin, Raytcho Lazarov, Joseph Pasciak, Zhi Zhou. Error
analysis of semidiscrete finite element methods for
inhomogeneous time-fractional diffusion. IMA Journal of Numerical Analysis
2015;35(2): 561--582.
8. Bangti
Jin, William Rundell. A tutorial on inverse problems in anomalous diffusion
process. Inverse Problems 2015;31(3), 035003, 40 pp.
9. Yalchin Efendiev,
Bangti Jin, Michael Prescho, Xiaosi Tan. Multilevel
Markov chain Monte Carlo method for high-contrast single-phase flow problems.
Communications in Computational Physics 2015;17(1): 259--286.
10. Bangti
Jin, Raytcho Lazarov, Yikan
Liu, Zhi Zhou. The Galerkin finite element method for
a multi-term time-fractional diffusion equation. Journal of Computational
Physics 2015;281: 825--843.
11. Zhiyuan
Sun, Yuling Jiao, Bangti Jin, Xiliang Lu. Numerical
identification of a sparse Robin coefficient. Advances in Computational
Mathematics 2015;41(1): 131--148.
2014
1. Matthias
Gehre, Bangti Jin, Xiliang
Lu. An analysis of finite element approximation of electrical impedance
tomography. Inverse Problems 2014;30(4), 045013 (24 pp).
2. Bangti
Jin, Raytcho Lazarov, Joseph Pasciak, Zhi Zhou. Error
analysis of a finite element method for a space-fractional parabolic equation.
SIAM Journal on Numerical Analysis 2014; 52(5): 2272--2294.
3. Matthias
Gehre, Bangti Jin. Expectation propagation for
nonlinear inverse problems -- with an application to electrical impedance
tomography. Journal of Computational Physics 2014; 259: 513--535.
4. Kazufumi Ito, Bangti Jin, Tomoya Takeuchi.
Multi-parameter Tikhonov regularization -- an augmented approach. Chinese
Annals of Mathematics, Series B, 2014; 35B(3):
383--398.
2013
1. Kazufumi Ito, Bangti Jin, Jun Zou. A direct
sampling method for the inverse electromagnetic medium scattering problem.
Inverse Problems 2013;29(9): 095018, 19 pp.
2. Kazufumi Ito, Bangti Jin, Jun Zou. A two-stage
method for inverse medium scattering. Journal of Computational Physics 2013;
237: 211--223.
3. Bangti
Jin, Raytcho Lazarov, Zhi Zhou. Error estimates for a
semidiscrete finite element method for fractional
order parabolic equations, SIAM Journal on Numerical Analysis 2013;51(1):
445--466.
2012
1. Bangti Jin,
Peter Maass. Sparsity regularization for parameter identification problems.
Inverse Problems 2012; 28(12): 123001 (70 pp.)
2. Bangti
Jin, Yubo Zhao, Jun Zou. Iterative parameter choice by discrepancy principle.
IMA Journal of Numerical Analysis 2012;32(4):1714--1732.
3. Bangti
Jin, Peter Maass. An analysis of electrical impedance tomography with
applications to Tikhonov regularization. ESAIM: Control, Optimisation
and Calculus of Variations 2012;18(4): 1027--1048.
4. Bangti
Jin, William Rundell. An inverse problem for a one-dimensional time-fractional
diffusion equation. Inverse Problems 2012;28(7): 075010 (19 pp.)
5. Bangti
Jin, William Rundell. An inverse Sturm-Liouville problem with a fractional
derivative. Journal of Computational Physics 2012;231(14): 4954--4966.
6. Christian
Clason, Bangti Jin. A semi-smooth Newton method for nonlinear parameter
identification problems with impulsive noise. SIAM Journal on Imaging Sciences
2012;5(2): 505--536.
7. Kazufumi Ito, Bangti Jin, Jun Zou. A direct
sampling method to inverse medium scattering problem. Inverse Problems
2012;28(2): 025003 (11 pp.).
8. Bangti
Jin. A variational Bayesian method to inverse problems with impulsive noise.
Journal of Computational Physics 2012;231(2):423--435.
9. Bangti
Jin, Taufiquar Khan, Peter Maass. A reconstruction
algorithm for electrical impedance tomography based on sparsity regularization.
International Journal for Numerical Methods in Engineering 2012;89(3):337--353.
10. Bangti
Jin, Xiliang Lu. Numerical identification of a Robin
coefficient in parabolic problems. Mathematics of Computation
2012;81(279):1369--1398.
11. Matthias
Gehre, Tobias Kluth, Antti Lipponen, Bangti Jin, Aku
Seppanen, Jari Kaipio, Peter Maass. Sparsity
reconstruction in electrical impedance tomography: an experimental evaluation.
Journal of Computational and Applied Mathematics 2012;236(8):2126--2136.
2011
1. Kazufumi Ito, Bangti Jin. A new approach to
nonlinear constrained Tikhonov regularization. Inverse Problems 2011;27(10):
105005(23 pp.).
2. Kazufumi Ito, Bangti Jin, Tomoya Takeuchi. A
regularization parameter for nonsmooth Tikhonov
regularization. SIAM Journal on Scientific Computing 2011;33(3):1415--1438.
3. Kazufumi Ito, Bangti Jin, Jun Zou. A new choice
rule for regularization parameters in Tikhonov regularization. Applicable
Analysis 2011;90(10): 1521--1544.
4. Kazufumi Ito, Bangti Jin, Tomoya Takeuchi.
Multi-parameter Tikhonov regularization, Methods and Applications of Analysis
2011;18(1): 31--46.
2010
1. Bangti
Jin, Dirk A Lorenz. Heuristic parameter-choice rules for convex variational
regularization based on error estimate. SIAM Journal on Numerical Analysis
2010;48(3):1208--1229.
2. Bangti
Jin, Jun Zou. Hierarchical Bayesian inference for ill-posed problems via
variational method. Journal of Computational Physics 2010;229(19):7317--7343.
3. Christian
Clason, Bangti Jin, Karl Kunisch. A duality-based splitting method for l1-TV
image restoration with automatic regularization parameter choice, SIAM Journal
on Scientific Computing 2010;32(3):1484-1505.
4. Christian
Clason, Bangti Jin, Karl Kunisch. A semismooth Newton method for L1 data
fitting with automatic choice of regularization parameters and noise
calibration, SIAM Journal on Imaging Sciences 2010;3(2):199--231.
5. Bangti
Jin, Jun Zou. Numerical estimation of the Robin coefficient in a stationary
diffusion equation. IMA Journal of Numerical Analysis 2010;30(3): 677--701.
6. Wen
Chen, Zoujia Fu, Bangti Jin. A truly boundary-only meshfree
method for inhomogeneous problems based on recursive composite multiple
reciprocity technique. Engineering Analysis with Boundary Elements 2010; 34(3):
196--205.
Before
2010
1. Bangti
Jin, Dirk Lorenz, Stefan Schiffler. Elastic-net regularization: error estimates
and active set methods, Inverse Problems 2009;25(11): 115022 (26pp).
2. Bangti
Jin, Jun Zou. Numerical estimation of piecewise constant Robin coefficient.
SIAM Journal on Control and Optimization 2009;48(3): 1977--2002.
3. Bangti
Jin, Jun Zou. Augmented Tikhonov regularization. Inverse Problems 2009;25(2):
0255001 (25pp).
4. Bangti
Jin. Fast Bayesian approach for parameter estimation. International Journal for
Numerical Methods in Engineering 2008;76(2):230--252.
5. Bangti
Jin, Jun Zou. Inversion of Robin coefficient by a spectral stochastic finite
element approach. Journal of Computational Physics 2008; 227(6): 3282--3306.
6. Bangti
Jin, Jun Zou. A Bayesian approach to the ill-posed Cauchy problem of
steady-state heat conduction. International Journal for Numerical Methods in
Engineering 2008;76(4): 521--544.
7. Bangti
Jin, Yao Zheng. A meshless method for some inverse problems associated with the
Helmholtz equation. Computer Methods in Applied Mechanics and Engineering 2006;
195(19-22): 2270--2288.
8. Bangti
Jin, Yao Zheng. Boundary knot method for the Cauchy problem associated with the
inhomogeneous Helmholtz equation. Engineering Analysis with Boundary Elements
2005; 29(10): 925--935.
9. Bangti
Jin, Yao Zheng. Boundary knot method for some inverse problems associated with
the Helmholtz equation. International Journal for Numerical Methods in
Engineering 2005; 62(12):1636--1651.