Boundary knot method based on geodesic distance for anisotropic problems. - Bangti Jin; Wen Chen (J. Comput. Phys., 2006)

Inversion of Robin coefficient by a spectral stochastic finite element approach. - Bangti Jin; Jun Zou 003 (J. Comput. Phys., 2008)

Numerical Estimation of Piecewise Constant Robin Coefficient. - Bangti Jin; Jun Zou 003 (SIAM J. Control. Optim., 2009)

Hierarchical Bayesian inference for Ill-posed problems via variational method. - Bangti Jin; Jun Zou 003 (J. Comput. Phys., 2010)

A Semismooth Newton Method for L1 Data Fitting with Automatic Choice of Regularization Parameters and Noise Calibration. - Christian Clason; Bangti Jin; Karl Kunisch (SIAM J. Imaging Sci., 2010)

Heuristic Parameter-Choice Rules for Convex Variational Regularization Based on Error Estimates. - Bangti Jin; Dirk A. Lorenz (SIAM J. Numer. Anal., 2010)

A Duality-Based Splitting Method for l1-TV Image Restoration with Automatic Regularization Parameter Choice. - Christian Clason; Bangti Jin; Karl Kunisch (SIAM J. Sci. Comput., 2010)

Multi-Parameter Tikhonov Regularization - Kazufumi Ito; Bangti Jin; Tomoya Takeuchi (CoRR, 2011)

A Regularization Parameter for Nonsmooth Tikhonov Regularization. - Kazufumi Ito; Bangti Jin; Tomoya Takeuchi (SIAM J. Sci. Comput., 2011)

Galerkin FEM for Fractional Order Parabolic Equations with Initial Data in H - s , 0 ≤ s ≤ 1. - Bangti Jin; Raytcho D. Lazarov; Joseph E. Pasciak; Zhi Zhou 002 (NAA, 2012)

Sparsity reconstruction in electrical impedance tomography: An experimental evaluation. - Matthias Gehre; Tobias Kluth; Antti Lipponen; Bangti Jin; Aku Seppänen; Jari P. Kaipio; Peter Maass (J. Comput. Appl. Math., 2012)

A variational Bayesian method to inverse problems with impulsive noise. - Bangti Jin (J. Comput. Phys., 2012)

An inverse Sturm-Liouville problem with a fractional derivative. - Bangti Jin; William Rundell (J. Comput. Phys., 2012)

Numerical identification of a Robin coefficient in parabolic problems. - Bangti Jin; Xiliang Lu (Math. Comput., 2012)

A Semismooth Newton Method for Nonlinear Parameter Identification Problems with Impulsive Noise. - Christian Clason; Bangti Jin (SIAM J. Imaging Sci., 2012)

Gradient-based estimation of Manning's friction coefficient from noisy data. - Victor M. Calo; Nathan O. Collier; Matthias Gehre; Bangti Jin; Hany Radwan; Mauricio Santillana (J. Comput. Appl. Math., 2013)

A two-stage method for inverse medium scattering. - Kazufumi Ito; Bangti Jin; Jun Zou 003 (J. Comput. Phys., 2013)

Error Estimates for a Semidiscrete Finite Element Method for Fractional Order Parabolic Equations. - Bangti Jin; Raytcho D. Lazarov; Zhi Zhou 002 (SIAM J. Numer. Anal., 2013)

A Primal Dual Active Set with Continuation Algorithm for the ell^0-Regularized Optimization Problem. - Yuling Jiao; Bangti Jin; Xiliang Lu (CoRR, 2014)

Expectation propagation for nonlinear inverse problems - with an application to electrical impedance tomography. - Matthias Gehre; Bangti Jin (J. Comput. Phys., 2014)

Error Analysis of a Finite Element Method for the Space-Fractional Parabolic Equation. - Bangti Jin; Raytcho D. Lazarov; Joseph E. Pasciak; Zhi Zhou 002 (SIAM J. Numer. Anal., 2014)

Numerical identification of a sparse Robin coefficient. - Zhiyuan Sun; Yuling Jiao; Bangti Jin; Xiliang Lu (Adv. Comput. Math., 2015)

On the sectorial property of the Caputo derivative operator. - Kazufumi Ito; Bangti Jin; Tomoya Takeuchi (Appl. Math. Lett., 2015)

A variational Bayesian approach for inverse problems with skew-t error distributions. - Nilabja Guha; Xiaoqing Wu; Yalchin Efendiev; Bangti Jin; Bani K. Mallick (J. Comput. Phys., 2015)

The Galerkin finite element method for a multi-term time-fractional diffusion equation. - Bangti Jin; Raytcho D. Lazarov; Yikan Liu; Zhi Zhou 002 (J. Comput. Phys., 2015)

Variational formulation of problems involving fractional order differential operators. - Bangti Jin; Raytcho D. Lazarov; Joseph E. Pasciak; William Rundell (Math. Comput., 2015)

An analysis of the Rayleigh-Stokes problem for a generalized second-grade fluid. - Emilia G. Bazhlekova; Bangti Jin; Raytcho D. Lazarov; Zhi Zhou 002 (Numerische Mathematik, 2015)

A simple finite element method for boundary value problems with a Riemann-Liouville derivative. - Bangti Jin; Raytcho D. Lazarov; Xiliang Lu; Zhi Zhou 002 (J. Comput. Appl. Math., 2016)

The Linearized Inverse Problem in Multifrequency Electrical Impedance Tomography. - Giovanni S. Alberti; Habib Ammari; Bangti Jin; Jin Keun Seo; Wenlong Zhang (SIAM J. Imaging Sci., 2016)

A Petrov-Galerkin Finite Element Method for Fractional Convection-Diffusion Equations. - Bangti Jin; Raytcho D. Lazarov; Zhi Zhou 002 (SIAM J. Numer. Anal., 2016)

Two Fully Discrete Schemes for Fractional Diffusion and Diffusion-Wave Equations with Nonsmooth Data. - Bangti Jin; Raytcho D. Lazarov; Zhi Zhou 002 (SIAM J. Sci. Comput., 2016)

Preface: Numerical Analysis of Fractional Differential Equations. - Bangti Jin; Raytcho D. Lazarov; Petr N. Vabishchevich (Comput. Methods Appl. Math., 2017)

On nonnegativity preservation in finite element methods for subdiffusion equations. - Bangti Jin; Raytcho D. Lazarov; Vidar Thomée; Zhi Zhou 002 (Math. Comput., 2017)

Correction of High-Order BDF Convolution Quadrature for Fractional Evolution Equations. - Bangti Jin; Buyang Li; Zhi Zhou 002 (SIAM J. Sci. Comput., 2017)

Iterative Soft/Hard Thresholding With Homotopy Continuation for Sparse Recovery. - Yuling Jiao; Bangti Jin; Xiliang Lu (IEEE Signal Process. Lett., 2017)

Group Sparse Recovery via the ℓ0(ℓ2) Penalty: Theory and Algorithm. - Yuling Jiao; Bangti Jin; Xiliang Lu (IEEE Trans. Signal Process., 2017)

Space-Time Petrov-Galerkin FEM for Fractional Diffusion Problems. - Beiping Duan; Bangti Jin; Raytcho D. Lazarov; Joseph E. Pasciak; Zhi Zhou 002 (Comput. Methods Appl. Math., 2018)

Discrete maximal regularity of time-stepping schemes for fractional evolution equations. - Bangti Jin; Buyang Li; Zhi Zhou 002 (Numerische Mathematik, 2018)

Numerical Analysis of Nonlinear Subdiffusion Equations. - Bangti Jin; Buyang Li; Zhi Zhou 002 (SIAM J. Numer. Anal., 2018)

Incomplete Iterative Solution of the Subdiffusion Problem. - Bangti Jin; Zhi Zhou 002 (CoRR, 2019)

Wasserstein Gradient Flow Formulation of the Time-Fractional Fokker-Planck Equation. - Manh Hong Duong; Bangti Jin (CoRR, 2019)

Regularized Linear Inversion with Randomized Singular Value Decomposition. - Kazufumi Ito; Bangti Jin (CoRR, 2019)

A Parameter Choice Rule for Tikhonov Regularization Based on Predictive Risk. - Federico Benvenuto; Bangti Jin (CoRR, 2019)

Subdiffusion with a time-dependent coefficient: Analysis and numerical solution. - Bangti Jin; Buyang Li; Zhi Zhou 002 (Math. Comput., 2019)

Quantifying Model Uncertainty in Inverse Problems via Bayesian Deep Gradient Descent. - Riccardo Barbano; Chen Zhang 023; Simon R. Arridge; Bangti Jin (ICPR, 2020)

L1 data fitting for robust reconstruction in magnetic particle imaging: quantitative evaluation on Open MPI dataset. - Tobias Kluth; Bangti Jin (CoRR, 2020)

On the Discrepancy Principle for Stochastic Gradient Descent. - Tim Jahn; Bangti Jin (CoRR, 2020)

An Inverse Potential Problem for Subdiffusion: Stability and Reconstruction. - Bangti Jin; Zhi Zhou 002 (CoRR, 2020)

Quantifying Sources of Uncertainty in Deep Learning-Based Image Reconstruction. - Riccardo Barbano; Zeljko Kereta; Chen Zhang 023; Andreas Hauptmann; Simon R. Arridge; Bangti Jin (CoRR, 2020)

Subdiffusion with time-dependent coefficients: improved regularity and second-order time stepping. - Bangti Jin; Buyang Li; Zhi Zhou 002 (Numerische Mathematik, 2020)

Incomplete iterative solution of subdiffusion. - Bangti Jin; Zhi Zhou 002 (Numerische Mathematik, 2020)

On the Convergence of Stochastic Gradient Descent for Nonlinear Ill-Posed Problems. - Bangti Jin; Zehui Zhou; Jun Zou 003 (SIAM J. Optim., 2020)

Conditional Variational Autoencoder for Learned Image Reconstruction. - Chen Zhang 023; Riccardo Barbano; Bangti Jin (Comput., 2021)

Recovering the Potential in One-Dimensional Time-Fractional Diffusion with Unknown Initial Condition and Source. - Bangti Jin; Zhi Zhou 002 (CoRR, 2021)

Recovering Multiple Fractional Orders in Time-Fractional Diffusion in an Unknown Medium. - Bangti Jin; Yavar Kian (CoRR, 2021)

Stochastic EM methods with Variance Reduction for Penalised PET Reconstructions. - Zeljko Kereta; Robert Twyman; Simon R. Arridge; Kris Thielemans; Bangti Jin (CoRR, 2021)

Unsupervised Knowledge-Transfer for Learned Image Reconstruction. - Riccardo Barbano; Zeljko Kereta; Andreas Hauptmann; Simon R. Arridge; Bangti Jin (CoRR, 2021)

An Analysis of Stochastic Variance Reduced Gradient for Linear Inverse Problems. - Bangti Jin; Zehui Zhou; Jun Zou 003 (CoRR, 2021)

Recovery of a Space-Time Dependent Diffusion Coefficient in Subdiffusion: Stability, Approximation and Error Analysis. - Bangti Jin; Zhi Zhou 002 (CoRR, 2021)

Is Deep Image Prior in Need of a Good Education? - Riccardo Barbano; Johannes Leuschner; Maximilian Schmidt; Alexander Denker; Andreas Hauptmann; Peter Maaß; Bangti Jin (CoRR, 2021)

On the Saturation Phenomenon of Stochastic Gradient Descent for Linear Inverse Problems. - Bangti Jin; Zehui Zhou; Jun Zou 003 (SIAM/ASA J. Uncertain. Quantification, 2021)

Numerical Estimation of a Diffusion Coefficient in Subdiffusion. - Bangti Jin; Zhi Zhou 002 (SIAM J. Control. Optim., 2021)

Reconstruction of a Space-Time-Dependent Source in Subdiffusion Models via a Perturbation Approach. - Bangti Jin; Yavar Kian; Zhi Zhou 002 (SIAM J. Math. Anal., 2021)

Error Analysis of Finite Element Approximations of Diffusion Coefficient Identification for Elliptic and Parabolic Problems. - Bangti Jin; Zhi Zhou 002 (SIAM J. Numer. Anal., 2021)

A Probabilistic Deep Image Prior for Computational Tomography. - Javier Antorán; Riccardo Barbano; Johannes Leuschner; José Miguel Hernández-Lobato; Bangti Jin (CoRR, 2022)

Convergence Rate Analysis of Galerkin Approximation of Inverse Potential Problem. - Bangti Jin; Xiliang Lu; Qimeng Quan; Zhi Zhou 002 (CoRR, 2022)

Imaging Conductivity from Current Density Magnitude using Neural Networks. - Bangti Jin; Xiyao Li; Xiliang Lu (CoRR, 2022)

Bayesian Experimental Design for Computed Tomography with the Linearised Deep Image Prior. - Riccardo Barbano; Johannes Leuschner; Javier Antorán; Bangti Jin; José Miguel Hernández-Lobato (CoRR, 2022)

Recovery of a Distributed Order Fractional Derivative in an Unknown Medium. - Bangti Jin; Yavar Kian (CoRR, 2022)

An Educated Warm Start for Deep Image Prior-Based Micro CT Reconstruction. - Riccardo Barbano; Johannes Leuschner; Maximilian Schmidt; Alexander Denker; Andreas Hauptmann; Peter Maass; Bangti Jin (IEEE Trans. Computational Imaging, 2022)

Recovery of the Order of Derivation for Fractional Diffusion Equations in an Unknown Medium. - Bangti Jin; Yavar Kian (SIAM J. Appl. Math., 2022)

Imaging Anisotropic Conductivities from Current Densities. - Huan Liu; Bangti Jin; Xiliang Lu (SIAM J. Imaging Sci., 2022)

SVD-DIP: Overcoming the Overfitting Problem in DIP-based CT Reconstruction. - Marco Nittscher; Michael Falk Lameter; Riccardo Barbano; Johannes Leuschner; Bangti Jin; Peter Maass (MIDL, 2023)

Fast and Painless Image Reconstruction in Deep Image Prior Subspaces. - Riccardo Barbano; Javier Antorán; Johannes Leuschner; José Miguel Hernández-Lobato; Zeljko Kereta; Bangti Jin (CoRR, 2023)

Hybrid Neural-Network FEM Approximation of Diffusion Coefficient in Elliptic and Parabolic Problems. - Siyu Cen; Bangti Jin; Qimeng Quan; Zhi Zhou 002 (CoRR, 2023)

Recovery of Multiple Parameters in Subdiffusion from One Lateral Boundary Measurement. - Siyu Cen; Bangti Jin; Yikan Liu; Zhi Zhou 002 (CoRR, 2023)

Solving Elliptic Optimal Control Problems using Physics Informed Neural Networks. - Bangti Jin; Ramesh Sau; Luowei Yin; Zhi Zhou 002 (CoRR, 2023)

Score-Based Generative Models for PET Image Reconstruction. - Imraj RD Singh; Alexander Denker; Riccardo Barbano; Zeljko Kereta; Bangti Jin; Kris Thielemans; Peter Maass; Simon R. Arridge (CoRR, 2023)

Steerable Conditional Diffusion for Out-of-Distribution Adaptation in Imaging Inverse Problems. - Riccardo Barbano; Alexander Denker; Hyungjin Chung; Tae-Hoon Roh; Simon Arrdige; Peter Maass; Bangti Jin; Jong Chul Ye (CoRR, 2023)

Electrical Impedance Tomography: A Fair Comparative Study on Deep Learning and Analytic-based Approaches. - Derick Nganyu Tanyu; Jianfeng Ning; Andreas Hauptmann; Bangti Jin; Peter Maass (CoRR, 2023)

Numerical Recovery of a Time-Dependent Potential in Subdiffusion. - Bangti Jin; Kwancheol Shin; Zhi Zhou 002 (CoRR, 2023)

Solving Inverse Obstacle Scattering Problem with Latent Surface Representations. - Junqing Chen; Bangti Jin; Haibo Liu (CoRR, 2023)

Learning Coarse Propagators in Parareal Algorithm. - Bangti Jin; Qingle Lin; Zhi Zhou 002 (CoRR, 2023)

An Investigation of Stochastic Variance Reduction Algorithms for Relative Difference Penalized 3D PET Image Reconstruction. - 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 (IEEE Trans. Medical Imaging, 2023)

Uncertainty Estimation for Computed Tomography with a Linearised Deep Image Prior. - Javier Antorán; Riccardo Barbano; Johannes Leuschner; José Miguel Hernández-Lobato; Bangti Jin (Trans. Mach. Learn. Res., 2023)

On the Convergence of Stochastic Gradient Descent for Linear Inverse Problems in Banach Spaces. - Bangti Jin; Zeljko Kereta (SIAM J. Imaging Sci., 2023)

Inverse Problems for Subdiffusion from Observation at an Unknown Terminal Time. - Bangti Jin; Yavar Kian; Zhi Zhou 002 (SIAM J. Appl. Math., 2023)

Solving Elliptic Problems with Singular Sources Using Singularity Splitting Deep Ritz Method. - Tianhao Hu; Bangti Jin; Zhi Zhou 002 (SIAM J. Sci. Comput., 2023)

Electrical impedance tomography with deep Calderón method. - Siyu Cen; Bangti Jin; Kwancheol Shin; Zhi Zhou 002 (J. Comput. Phys., 2023)

Discontinuous polynomial approximation in electrical impedance tomography with total variational regularization. - Bangti Jin; Yifeng Xu; Jingrong Yang; Kai Zhang (Commun. Nonlinear Sci. Numer. Simul., 2024)

Inverse Coefficient Problem for One-Dimensional Subdiffusion with Data on Disjoint Sets in Time. - Siyu Cen; Bangti Jin; Yavar Kian; Eric Soccorsi; Rachid Zarouf; Zhi Zhou 002 (CoRR, 2024)

Numerical Recovery of the Diffusion Coefficient in Diffusion Equations from Terminal Measurement. - Bangti Jin; Xiliang Lu; Qimeng Quan; Zhi Zhou 002 (CoRR, 2024)

Point Source Identification Using Singularity Enriched Neural Networks. - Tianhao Hu; Bangti Jin; Zhi Zhou 002 (CoRR, 2024)

On an Inverse Problem of the Generalized Bathtub Model of Network Trip Flows. - Kuang Huang; Bangti Jin; Zhi Zhou 002 (CoRR, 2024)

Theory and Fast Learned Solver for ℓ1-TV Regularization. - Xinling Liu; Jianjun Wang; Bangti Jin (CoRR, 2024)

An adaptive phase-field method for structural topology optimization. - Bangti Jin; Jing Li; Yifeng Xu; Shengfeng Zhu (J. Comput. Phys., 2024)

On the approximation of bi-Lipschitz maps by invertible neural networks. - Bangti Jin; Zehui Zhou; Jun Zou 003 (Neural Networks, 2024)

Early Stopping of Untrained Convolutional Neural Networks. - Tim Jahn; Bangti Jin (SIAM J. Imaging Sci., 2024)

Solving Poisson Problems in Polygonal Domains with Singularity Enriched Physics Informed Neural Networks. - Tianhao Hu; Bangti Jin; Zhi Zhou 002 (SIAM J. Sci. Comput., 2024)

Image Reconstruction via Deep Image Prior Subspaces. - Riccardo Barbano; Javier Antorán; Johannes Leuschner; José Miguel Hernández-Lobato; Bangti Jin; Zeljko Kereta (Trans. Mach. Learn. Res., 2024)

Conductivity Imaging from Internal Measurements with Mixed Least-Squares Deep Neural Networks. - Bangti Jin; Xiyao Li; Qimeng Quan; Zhi Zhou 002 (SIAM J. Imaging Sci., 2024)

The discrete inverse conductivity problem solved by the weights of an interpretable neural network. - Elena Beretta; Maolin Deng; Alberto Gandolfi; Bangti Jin (J. Comput. Phys., 2025)

Imaging anisotropic conductivity from internal measurements with mixed least-squares deep neural networks. - Siyu Cen; Bangti Jin; Xiyao Li; Zhi Zhou 002 (J. Comput. Phys., 2025)

An iterative deep Ritz method for monotone elliptic problems. - Tianhao Hu; Bangti Jin; Fengru Wang (J. Comput. Phys., 2025)

Stochastic Convergence Analysis of the Inverse Potential Problem. - Bangti Jin; Qimeng Quan; Wenlong Zhang (SIAM/ASA J. Uncertain. Quantification, 2025)

Point Source Identification in Subdiffusion from A Posteriori Internal Measurement. - Kuang Huang; Bangti Jin; Yavar Kian; Georges Sadaka; Zhi Zhou 002 (SIAM J. Appl. Math., 2025)

Iterative Direct Sampling Method for Elliptic Inverse Problems with Limited Cauchy Data. - Kazufumi Ito; Bangti Jin; Fengru Wang; Jun Zou 003 (SIAM J. Imaging Sci., 2025)

Identification of a Spatially-Dependent Variable Order in One-Dimensional Subdiffusion. - Jiho Hong; Bangti Jin; Yavar Kian (SIAM J. Math. Anal., 2025)

Regularity Analysis and High-Order Time Stepping Scheme for Quasilinear Subdiffusion. - Bangti Jin; Qimeng Quan; Barbara I. Wohlmuth; Zhi Zhou 002 (SIAM J. Numer. Anal., 2025)

Optimizing Coarse Propagators in Parareal Algorithms. - Bangti Jin; Qingle Lin; Zhi Zhou 002 (SIAM J. Sci. Comput., 2025)

Adaptive Approximations of Inclusions in a Semilinear Elliptic Problem Related to Cardiac Electrophysiology. - Bangti Jin; Fengru Wang; Yifeng Xu (CoRR, 2025)

Stable Determination and Reconstruction of a Quasilinear Term in an Elliptic Equation. - Jason Choy; Maolin Deng; Bangti Jin; Yavar Kian (CoRR, 2025)

On the Crouzeix-Raviart Finite Element Approximation of Phase-Field Dependent Topology Optimization in Stokes Flow. - Bangti Jin; Jing Li; Yifeng Xu; Shengfeng Zhu (CoRR, 2025)

Convergence Analysis of an Adaptive Nonconforming FEM for Phase-Field Dependent Topology Optimization in Stokes Flow. - Bangti Jin; Jing Li; Yifeng Xu; Shengfeng Zhu (CoRR, 2025)

Direct Algorithms for Reconstructing Small Conductivity Inclusions in Subdiffusion. - Jiho Hong; Bangti Jin; Zhizhang Wu (CoRR, 2025)

Deep asymptotic expansion method for solving singularly perturbed time-dependent reaction-advection-diffusion equations. - Qiao Zhu; Dmitrii Chaikovskii; Bangti Jin; Ye Zhang (CoRR, 2025)

Steerable Conditional Diffusion for Out-of-Distribution Adaptation in Medical Image Reconstruction. - Riccardo Barbano; Alexander Denker; Hyungjin Chung; Tae-Hoon Roh; Simon R. Arridge; Peter Maass; Bangti Jin; Jong Chul Ye (IEEE Trans. Medical Imaging, 2025)

Numerical Approximation and Analysis of the Inverse Robin Problem Using the Kohn-Vogelius Method. - Erik Burman; Siyu Cen; Bangti Jin; Zhi Zhou 002 (CoRR, 2025)

Simultaneous Identification of Coefficients and Source in a Subdiffusion Equation from One Passive Measurement. - Maolin Deng; Ali Feizmohammadi; Bangti Jin; Yavar Kian (CoRR, 2025)

Solving elliptic optimal control problems via neural networks and optimality system. - Yongcheng Dai; Bangti Jin; Ramesh Chandra Sau; Zhi Zhou 002 (Adv. Comput. Math., 2025)

Numerical Analysis of Unsupervised Learning Approaches for Parameter Identification in PDEs. - Siyu Cen; Bangti Jin; Qimeng Quan; Zhi Zhou 002 (CoRR, 2025)

Conditional Stability and Numerical Reconstruction of a Parabolic Inverse Source Problem Using Carleman Estimates. - Tianhao Hu; Xinchi Huang; Bangti Jin; Qimeng Quan; Zhi Zhou 002 (CoRR, 2025)