Bangti Jin

ORCID

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 92

Top Venues

Publications

Riccardo Barbano, Javier Antorán, Johannes Leuschner, José Miguel Hernández-Lobato, Bangti Jin, Zeljko Kereta
Image Reconstruction via Deep Image Prior Subspaces. Trans. Mach. Learn. Res. 2024 (2024)
Bangti Jin, Zehui Zhou, Jun Zou
On the approximation of bi-Lipschitz maps by invertible neural networks. Neural Networks 174 (2024)
Siyu Cen, Bangti Jin, Yavar Kian, Eric Soccorsi, Rachid Zarouf, Zhi Zhou
Inverse Coefficient Problem for One-Dimensional Subdiffusion with Data on Disjoint Sets in Time. CoRR (2024)
Bangti Jin, Jing Li, Yifeng Xu, Shengfeng Zhu
An adaptive phase-field method for structural topology optimization. J. Comput. Phys. 506 (2024)
Bangti Jin, Qimeng Quan, Barbara Wohlmuth, Zhi Zhou
Regularity Analysis and High-Order Time Stepping Scheme for Quasilinear Subdiffusion. CoRR (2024)
Tianhao Hu, Bangti Jin, Zhi Zhou
Solving Poisson Problems in Polygonal Domains with Singularity Enriched Physics Informed Neural Networks. SIAM J. Sci. Comput. 46 (4) (2024)
Bangti Jin, Xiyao Li, Qimeng Quan, Zhi Zhou
Conductivity Imaging from Internal Measurements with Mixed Least-Squares Deep Neural Networks. SIAM J. Imaging Sci. 17 (1) (2024)
Bangti Jin, Xiliang Lu, Qimeng Quan, Zhi Zhou
Numerical Recovery of the Diffusion Coefficient in Diffusion Equations from Terminal Measurement. CoRR (2024)
Tim Jahn, Bangti Jin
Early Stopping of Untrained Convolutional Neural Networks. CoRR (2024)
Bangti Jin, Yifeng Xu, Jingrong Yang, Kai Zhang
Discontinuous polynomial approximation in electrical impedance tomography with total variational regularization. Commun. Nonlinear Sci. Numer. Simul. 137 (2024)
Siyu Cen, Bangti Jin, Kwancheol Shin, Zhi Zhou
Electrical impedance tomography with deep Calderón method. J. Comput. Phys. 493 (2023)
Junqing Chen, Bangti Jin, Haibo Liu
Solving Inverse Obstacle Scattering Problem with Latent Surface Representations. CoRR (2023)
Siyu Cen, Bangti Jin, Qimeng Quan, Zhi Zhou
Hybrid Neural-Network FEM Approximation of Diffusion Coefficient in Elliptic and Parabolic Problems. CoRR (2023)
Siyu Cen, Bangti Jin, Kwancheol Shin, Zhi Zhou
Electrical Impedance Tomography with Deep Calderón Method. CoRR (2023)
Bangti Jin, Jing Li, Yifeng Xu, Shengfeng Zhu
An Adaptive Phase-Field Method for Structural Topology Optimization. CoRR (2023)
Imraj RD Singh, Alexander Denker, Riccardo Barbano, Zeljko Kereta, Bangti Jin, Kris Thielemans, Peter Maass, Simon R. Arridge
Score-Based Generative Models for PET Image Reconstruction. CoRR (2023)
Bangti Jin, Kwancheol Shin, Zhi Zhou
Numerical Recovery of a Time-Dependent Potential in Subdiffusion. CoRR (2023)
Marco Nittscher, Michael Lameter, Riccardo Barbano, Johannes Leuschner, Bangti Jin, Peter Maass
SVD-DIP: Overcoming the Overfitting Problem in DIP-based CT Reconstruction. CoRR (2023)
Robert Twyman, Simon R. Arridge, Zeljko Kereta, Bangti Jin, Ludovica Brusaferri, Sangtae Ahn, Charles W. Stearns, Brian F. Hutton, Irene A. Burger, Fotis Kotasidis, Kris Thielemans
An Investigation of Stochastic Variance Reduction Algorithms for Relative Difference Penalized 3D PET Image Reconstruction. IEEE Trans. Medical Imaging 42 (1) (2023)
Derick Nganyu Tanyu, Jianfeng Ning, Andreas Hauptmann, Bangti Jin, Peter Maass
Electrical Impedance Tomography: A Fair Comparative Study on Deep Learning and Analytic-based Approaches. CoRR (2023)
Javier Antorán, Riccardo Barbano, Johannes Leuschner, José Miguel Hernández-Lobato, Bangti Jin
Uncertainty Estimation for Computed Tomography with a Linearised Deep Image Prior. Trans. Mach. Learn. Res. 2023 (2023)
Bangti Jin, Yavar Kian, Zhi Zhou
Inverse Problems for Subdiffusion from Observation at an Unknown Terminal Time. SIAM J. Appl. Math. 83 (4) (2023)
Marco Nittscher, Michael Falk Lameter, Riccardo Barbano, Johannes Leuschner, Bangti Jin, Peter Maass
SVD-DIP: Overcoming the Overfitting Problem in DIP-based CT Reconstruction. MIDL (2023)
Siyu Cen, Bangti Jin, Yikan Liu, Zhi Zhou
Recovery of Multiple Parameters in Subdiffusion from One Lateral Boundary Measurement. CoRR (2023)
Bangti Jin, Zeljko Kereta
On the Convergence of Stochastic Gradient Descent for Linear Inverse Problems in Banach Spaces. SIAM J. Imaging Sci. 16 (2) (2023)
Bangti Jin, Xiyao Li, Qimeng Quan, Zhi Zhou
Conductivity Imaging from Internal Measurements with Mixed Least-Squares Deep Neural Networks. CoRR (2023)
Tianhao Hu, Bangti Jin, Zhi Zhou
Solving Poisson Problems in Polygonal Domains with Singularity Enriched Physics Informed Neural Networks. CoRR (2023)
Zeljko Kereta, Bangti Jin
On the Convergence of Stochastic Gradient Descent for Linear Inverse Problems in Banach Spaces. CoRR (2023)
Bangti Jin, Ramesh Sau, Luowei Yin, Zhi Zhou
Solving Elliptic Optimal Control Problems using Physics Informed Neural Networks. CoRR (2023)
Tianhao Hu, Bangti Jin, Zhi Zhou
Solving Elliptic Problems with Singular Sources Using Singularity Splitting Deep Ritz Method. SIAM J. Sci. Comput. 45 (4) (2023)
Bangti Jin, Zehui Zhou, Jun Zou
On the Approximation of Bi-Lipschitz Maps by Invertible Neural Networks. CoRR (2023)
Riccardo Barbano, Alexander Denker, Hyungjin Chung, Tae-Hoon Roh, Simon Arrdige, Peter Maass, Bangti Jin, Jong Chul Ye
Steerable Conditional Diffusion for Out-of-Distribution Adaptation in Imaging Inverse Problems. CoRR (2023)
Bangti Jin, Qingle Lin, Zhi Zhou
Learning Coarse Propagators in Parareal Algorithm. CoRR (2023)
Riccardo Barbano, Javier Antorán, Johannes Leuschner, José Miguel Hernández-Lobato, Zeljko Kereta, Bangti Jin
Fast and Painless Image Reconstruction in Deep Image Prior Subspaces. CoRR (2023)
Tianhao Hu, Bangti Jin, Zhi Zhou
Solving Elliptic Problems with Singular Sources using Singularity Splitting Deep Ritz Method. CoRR (2022)
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 Trans. Computational Imaging 8 (2022)
Javier Antorán, Riccardo Barbano, Johannes Leuschner, José Miguel Hernández-Lobato, Bangti Jin
A Probabilistic Deep Image Prior for Computational Tomography. CoRR (2022)
Bangti Jin, Xiyao Li, Xiliang Lu
Imaging Conductivity from Current Density Magnitude using Neural Networks. CoRR (2022)
Bangti Jin, Yavar Kian
Recovery of a Distributed Order Fractional Derivative in an Unknown Medium. CoRR (2022)
Bangti Jin, Yavar Kian
Recovery of the Order of Derivation for Fractional Diffusion Equations in an Unknown Medium. SIAM J. Appl. Math. 82 (3) (2022)
Huan Liu, Bangti Jin, Xiliang Lu
Imaging Anisotropic Conductivities from Current Densities. CoRR (2022)
Huan Liu, Bangti Jin, Xiliang Lu
Imaging Anisotropic Conductivities from Current Densities. SIAM J. Imaging Sci. 15 (2) (2022)
Bangti Jin, Xiliang Lu, Qimeng Quan, Zhi Zhou
Convergence Rate Analysis of Galerkin Approximation of Inverse Potential Problem. CoRR (2022)
Riccardo Barbano, Johannes Leuschner, Javier Antorán, Bangti Jin, José Miguel Hernández-Lobato
Bayesian Experimental Design for Computed Tomography with the Linearised Deep Image Prior. CoRR (2022)
Bangti Jin, Yavar Kian, Zhi Zhou
Inverse Problems for Subdiffusion from Observation at an Unknown Terminal Time. CoRR (2022)
Bangti Jin, Yavar Kian
Recovery of the Order of Derivation for Fractional Diffusion Equations in an Unknown Medium. CoRR (2021)
Bangti Jin, Yavar Kian, Zhi Zhou
Reconstruction of a Space-Time Dependent Source in Subdiffusion Models via a Perturbation Approach. CoRR (2021)
Bangti Jin, Yavar Kian
Recovering Multiple Fractional Orders in Time-Fractional Diffusion in an Unknown Medium. CoRR (2021)
Bangti Jin, Zhi Zhou
Recovery of a Space-Time Dependent Diffusion Coefficient in Subdiffusion: Stability, Approximation and Error Analysis. CoRR (2021)
Bangti Jin, Zhi Zhou
Error Analysis of Finite Element Approximations of Diffusion Coefficient Identification for Elliptic and Parabolic Problems. SIAM J. Numer. Anal. 59 (1) (2021)
Zeljko Kereta, Robert Twyman, Simon R. Arridge, Kris Thielemans, Bangti Jin
Stochastic EM methods with Variance Reduction for Penalised PET Reconstructions. CoRR (2021)
Bangti Jin, Zhi Zhou
Numerical Estimation of a Diffusion Coefficient in Subdiffusion. SIAM J. Control. Optim. 59 (2) (2021)
Riccardo Barbano, Johannes Leuschner, Maximilian Schmidt, Alexander Denker, Andreas Hauptmann, Peter Maaß, Bangti Jin
Is Deep Image Prior in Need of a Good Education? CoRR (2021)
Bangti Jin, Yavar Kian, Zhi Zhou
Reconstruction of a Space-Time-Dependent Source in Subdiffusion Models via a Perturbation Approach. SIAM J. Math. Anal. 53 (4) (2021)
Riccardo Barbano, Zeljko Kereta, Andreas Hauptmann, Simon R. Arridge, Bangti Jin
Unsupervised Knowledge-Transfer for Learned Image Reconstruction. CoRR (2021)
Chen Zhang, Riccardo Barbano, Bangti Jin
Conditional Variational Autoencoder for Learned Image Reconstruction. CoRR (2021)
Bangti Jin, Zehui Zhou, Jun Zou
On the Saturation Phenomenon of Stochastic Gradient Descent for Linear Inverse Problems. SIAM/ASA J. Uncertain. Quantification 9 (4) (2021)
Chen Zhang, Riccardo Barbano, Bangti Jin
Conditional Variational Autoencoder for Learned Image Reconstruction. Comput. 9 (11) (2021)
Bangti Jin, Zehui Zhou, Jun Zou
An Analysis of Stochastic Variance Reduced Gradient for Linear Inverse Problems. CoRR (2021)
Bangti Jin, Zhi Zhou
Recovering the Potential in One-Dimensional Time-Fractional Diffusion with Unknown Initial Condition and Source. CoRR (2021)
Tobias Kluth, Bangti Jin
L1 data fitting for robust reconstruction in magnetic particle imaging: quantitative evaluation on Open MPI dataset. CoRR (2020)
Riccardo Barbano, Chen Zhang, Simon R. Arridge, Bangti Jin
Quantifying Model Uncertainty in Inverse Problems via Bayesian Deep Gradient Descent. ICPR (2020)
Bangti Jin, Zhi Zhou
Incomplete iterative solution of subdiffusion. Numerische Mathematik 145 (3) (2020)
Bangti Jin, Zehui Zhou, Jun Zou
On the Convergence of Stochastic Gradient Descent for Nonlinear Ill-Posed Problems. SIAM J. Optim. 30 (2) (2020)
Bangti Jin, Zhi Zhou
Error Analysis of Finite Element Approximations of Diffusion Coefficient Identification for Elliptic and Parabolic Problems. CoRR (2020)
Bangti Jin, Zehui Zhou, Jun Zou
On the Saturation Phenomenon of Stochastic Gradient Descent for Linear Inverse Problems. CoRR (2020)
Bangti Jin, Buyang Li, Zhi Zhou
Subdiffusion with time-dependent coefficients: improved regularity and second-order time stepping. Numerische Mathematik 145 (4) (2020)
Riccardo Barbano, Zeljko Kereta, Chen Zhang, Andreas Hauptmann, Simon R. Arridge, Bangti Jin
Quantifying Sources of Uncertainty in Deep Learning-Based Image Reconstruction. CoRR (2020)
Bangti Jin, Buyang Li, Zhi Zhou
Subdiffusion with Time-Dependent Coefficients: Improved Regularity and Second-Order Time Stepping. CoRR (2020)
Tim Jahn, Bangti Jin
On the Discrepancy Principle for Stochastic Gradient Descent. CoRR (2020)
Bangti Jin, Zhi Zhou
An Inverse Potential Problem for Subdiffusion: Stability and Reconstruction. CoRR (2020)
Riccardo Barbano, Chen Zhang, Simon R. Arridge, Bangti Jin
Quantifying Model Uncertainty in Inverse Problems via Bayesian Deep Gradient Descent. CoRR (2020)
Federico Benvenuto, Bangti Jin
A Parameter Choice Rule for Tikhonov Regularization Based on Predictive Risk. CoRR (2019)
Bangti Jin, Zhi Zhou
Numerical Estimation of a Diffusion Coefficient in Subdiffusion. CoRR (2019)
Bangti Jin, Buyang Li, Zhi Zhou
Subdiffusion with a time-dependent coefficient: Analysis and numerical solution. Math. Comput. 88 (319) (2019)
Kazufumi Ito, Bangti Jin
Regularized Linear Inversion with Randomized Singular Value Decomposition. CoRR (2019)
Manh Hong Duong, Bangti Jin
Wasserstein Gradient Flow Formulation of the Time-Fractional Fokker-Planck Equation. CoRR (2019)
Bangti Jin, Zhi Zhou
Incomplete Iterative Solution of the Subdiffusion Problem. CoRR (2019)
Bangti Jin, Zehui Zhou, Jun Zou
On the Convergence of Stochastic Gradient Descent for Nonlinear Ill-Posed Problems. CoRR (2019)
Beiping Duan, Bangti Jin, Raytcho D. Lazarov, Joseph E. Pasciak, Zhi Zhou
Space-Time Petrov-Galerkin FEM for Fractional Diffusion Problems. Comput. Methods Appl. Math. 18 (1) (2018)
Bangti Jin, Buyang Li, Zhi Zhou
Discrete maximal regularity of time-stepping schemes for fractional evolution equations. Numerische Mathematik 138 (1) (2018)
Bangti Jin, Buyang Li, Zhi Zhou
Numerical Analysis of Nonlinear Subdiffusion Equations. SIAM J. Numer. Anal. 56 (1) (2018)
Bangti Jin, Raytcho D. Lazarov, Vidar Thomée, Zhi Zhou
On nonnegativity preservation in finite element methods for subdiffusion equations. Math. Comput. 86 (307) (2017)
Bangti Jin, Buyang Li, Zhi Zhou
Correction of High-Order BDF Convolution Quadrature for Fractional Evolution Equations. SIAM J. Sci. Comput. 39 (6) (2017)
Yuling Jiao, Bangti Jin, Xiliang Lu
) Penalty: Theory and Algorithm. IEEE Trans. Signal Process. 65 (4) (2017)
Bangti Jin, Raytcho D. Lazarov, Petr N. Vabishchevich
Preface: Numerical Analysis of Fractional Differential Equations. Comput. Methods Appl. Math. 17 (4) (2017)
Yuling Jiao, Bangti Jin, Xiliang Lu
Iterative Soft/Hard Thresholding With Homotopy Continuation for Sparse Recovery. IEEE Signal Process. Lett. 24 (6) (2017)
Bangti Jin, Raytcho D. Lazarov, Zhi Zhou
A Petrov-Galerkin Finite Element Method for Fractional Convection-Diffusion Equations. SIAM J. Numer. Anal. 54 (1) (2016)
Bangti Jin, Raytcho D. Lazarov, Xiliang Lu, Zhi Zhou
A simple finite element method for boundary value problems with a Riemann-Liouville derivative. J. Comput. Appl. Math. 293 (2016)
Yuling Jiao, Bangti Jin, Xiliang Lu
) Penalty: Theory and Algorithm. CoRR (2016)
Bangti Jin, Raytcho D. Lazarov, Zhi Zhou
Two Fully Discrete Schemes for Fractional Diffusion and Diffusion-Wave Equations with Nonsmooth Data. SIAM J. Sci. Comput. 38 (1) (2016)
Giovanni S. Alberti, Habib Ammari, Bangti Jin, Jin Keun Seo, Wenlong Zhang
The Linearized Inverse Problem in Multifrequency Electrical Impedance Tomography. SIAM J. Imaging Sci. 9 (4) (2016)
Bangti Jin, Raytcho D. Lazarov, Yikan Liu, Zhi Zhou
The Galerkin finite element method for a multi-term time-fractional diffusion equation. J. Comput. Phys. 281 (2015)
Emilia G. Bazhlekova, Bangti Jin, Raytcho D. Lazarov, Zhi Zhou
An analysis of the Rayleigh-Stokes problem for a generalized second-grade fluid. Numerische Mathematik 131 (1) (2015)
Kazufumi Ito, Bangti Jin, Tomoya Takeuchi
On the sectorial property of the Caputo derivative operator. Appl. Math. Lett. 47 (2015)
Bangti Jin, Raytcho D. Lazarov, Joseph E. Pasciak, William Rundell
Variational formulation of problems involving fractional order differential operators. Math. Comput. 84 (296) (2015)
Nilabja Guha, Xiaoqing Wu, Yalchin Efendiev, Bangti Jin, Bani K. Mallick
A variational Bayesian approach for inverse problems with skew-t error distributions. J. Comput. Phys. 301 (2015)
Zhiyuan Sun, Yuling Jiao, Bangti Jin, Xiliang Lu
Numerical identification of a sparse Robin coefficient. Adv. Comput. Math. 41 (1) (2015)
Yuling Jiao, Bangti Jin, Xiliang Lu
A Primal Dual Active Set with Continuation Algorithm for the \ell^0-Regularized Optimization Problem. CoRR (2014)
Bangti Jin, Raytcho D. Lazarov, Joseph E. Pasciak, Zhi Zhou
Error Analysis of a Finite Element Method for the Space-Fractional Parabolic Equation. SIAM J. Numer. Anal. 52 (5) (2014)

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Publication Activity (10 Years)

Top Topics

Top Venues

Bangti Jin