Books

  1. Kazufumi Ito, Bangti Jin. Inverse Problems: Tikhonov Theory and Algorithms, World Publishing, 2014

  2. Bangti Jin. Fractional Differential Equations. (Applied Mathematical Sciences, vol. 206). Springer 2021.


Preprint

  1. Bangti Jin, Xiyao Li, Xiliang Lu. Imaging conductivity from current density magnitude using neural networks.

  2. Javier Antoran, Riccardo Barbano, Jahannes Leuschner, Jose Miguel Hermandez-Lobato, Bangti Jin. A probabilistic deep image prior for computational tomography.

  3. Bangti Jin, Zhi Zhou. Recovery of a space-time dependent diffusion coefficient in subdiffusion: stability, approximation and error analysis

  4. Bangti Jin, Xiliang Lu, Qimeng Quan, Zhi Zhou. Convergence rate analysis of Galerkin approximation of inverse potential problem

  5. Riccardo Barbano, Zeljko Kereta, Andreas Hauptman, Simon Arridge, Bangti Jin. Unsupervised knowledge transfer for learned image reconstruction.

Recent publications

  1. Bangti Jin, Zehui Zhou, Jun Zou. An analysis of stochastic variance reduced gradient for linear inverse problems. Inverse Problems, in press.

  2. Bangti Jin, Yavar Kian. Recovery of the order of derivation in time-fractional differential equations in an unknown medium. SIAM Journal on Applied Mathematics, in press.

  3. Zeljko Kereta, Robert~Twyman, Simon~Arridge, Kris Thielemans, Bangti Jin. Stochastic EM methods with variance reduction for penalised PET reconstruction. Inverse Problems, in press

  4. Chen Zhang, Riccardo Barbano, Bangti Jin. Conditional variational autoencoder for image reconstruction. Computation, in press.

  5. 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).

  6. 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).

  7. Bangti Jin, Zehui Zhou, Jun Zou. On the saturation phenomenon of stochastic gradient descent for linear inverse problems, SIAM/ASA Journal on Uncertainty Quantification, in press.

  8. 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.

  9. Bangti Jin, Zhi Zhou. Numerical estimation of a diffusion coefficient in subdiffusion equations. SIAM Journal on Control and Optimization 2021;59(2): 1466--1496.

  10. 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.

  11. 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.

  12. Bangti Jin, Zhi Zhou. An inverse potential problem with subdiffusion: stability and reconstruction. Inverse Problems 2021;(1): 37, 015006, 26 pp.

  13. Tim Jahn, Bangti Jin. On the discrepancy principle for stochastic gradient descent. Inverse Problems 2020;36(9): 095009, 30 pp.

  14. Bangti Jin, Zhi Zhou. Incomplete iterative scheme for subdiffusion. Numerische Mathematik 2020;145(3): 693--725.

  15. 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.

  16. 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.

  17. 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.

  18. Federico Benvenuto, Bangti Jin. A regularization parameter for Tikhonov regularization based on predictive risk. Inverse Problems 2020; 36(6), 065004, 24 pp.

  19. 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.

  20. Bangti Jin, Yifeng Xu. Adaptive reconstruction for electrical impedance tomography with a piecewise constant conductivity. Inverse Problems 2020; 36(1): 014003, 28 pp.

  21. Chen Zhang, Simon Arridge, Bangti Jin. Expectation propagation for Poisson data. Inverse Problems 2019;35(8), 085006, 27 pp.

  22. 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.