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Bangti Jin
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2020 – today
- 2024
- [j60]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: 108166 (2024) - [j59]Bangti Jin, Jing Li, Yifeng Xu
An adaptive phase-field method for structural topology optimization. J. Comput. Phys. 506: 112932 (2024) - [j58]Bangti Jin
On the approximation of bi-Lipschitz maps by invertible neural networks. Neural Networks 174: 106214 (2024) - [j57]Bangti Jin
Conductivity Imaging from Internal Measurements with Mixed Least-Squares Deep Neural Networks. SIAM J. Imaging Sci. 17(1): 147-187 (2024) - [j56]Tianhao Hu, Bangti Jin
Solving Poisson Problems in Polygonal Domains with Singularity Enriched Physics Informed Neural Networks. SIAM J. Sci. Comput. 46(4): 369- (2024) - [j55]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) - [i58]Tim Jahn, Bangti Jin:
Early Stopping of Untrained Convolutional Neural Networks. CoRR abs/2402.04610 (2024) - [i57]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 abs/2403.11599 (2024) - [i56]Bangti Jin, Xiliang Lu, Qimeng Quan, Zhi Zhou:
Numerical Recovery of the Diffusion Coefficient in Diffusion Equations from Terminal Measurement. CoRR abs/2405.10708 (2024) - [i55]Bangti Jin, Qimeng Quan, Barbara Wohlmuth, Zhi Zhou:
Regularity Analysis and High-Order Time Stepping Scheme for Quasilinear Subdiffusion. CoRR abs/2407.19146 (2024) - [i54]Tianhao Hu, Bangti Jin, Zhi Zhou:
Point Source Identification Using Singularity Enriched Neural Networks. CoRR abs/2408.09143 (2024) - [i53]Kuang Huang, Bangti Jin, Zhi Zhou:
On an Inverse Problem of the Generalized Bathtub Model of Network Trip Flows. CoRR abs/2409.00619 (2024) - 2023
- [j54]Siyu Cen, Bangti Jin, Kwancheol Shin
Electrical impedance tomography with deep Calderón method. J. Comput. Phys. 493: 112427 (2023) - [j53]Bangti Jin, Yavar Kian
Inverse Problems for Subdiffusion from Observation at an Unknown Terminal Time. SIAM J. Appl. Math. 83(4): 1496-1517 (2023) - [j52]Bangti Jin, Zeljko Kereta
On the Convergence of Stochastic Gradient Descent for Linear Inverse Problems in Banach Spaces. SIAM J. Imaging Sci. 16(2): 671-705 (2023) - [j51]Tianhao Hu
Solving Elliptic Problems with Singular Sources Using Singularity Splitting Deep Ritz Method. SIAM J. Sci. Comput. 45(4): 2043- (2023) - [j50]Robert Twyman
An Investigation of Stochastic Variance Reduction Algorithms for Relative Difference Penalized 3D PET Image Reconstruction. IEEE Trans. Medical Imaging 42(1): 29-41 (2023) - [j49]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) - [c3]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: 617-642 - [i52]Zeljko Kereta, Bangti Jin:
On the Convergence of Stochastic Gradient Descent for Linear Inverse Problems in Banach Spaces. CoRR abs/2302.05197 (2023) - [i51]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 abs/2302.10279 (2023) - [i50]Siyu Cen, Bangti Jin, Qimeng Quan, Zhi Zhou:
Hybrid Neural-Network FEM Approximation of Diffusion Coefficient in Elliptic and Parabolic Problems. CoRR abs/2302.10773 (2023) - [i49]Marco Nittscher, Michael Lameter, Riccardo Barbano, Johannes Leuschner, Bangti Jin, Peter Maass:
SVD-DIP: Overcoming the Overfitting Problem in DIP-based CT Reconstruction. CoRR abs/2303.15748 (2023) - [i48]Bangti Jin, Xiyao Li, Qimeng Quan, Zhi Zhou:
Conductivity Imaging from Internal Measurements with Mixed Least-Squares Deep Neural Networks. CoRR abs/2303.16454 (2023) - [i47]Siyu Cen, Bangti Jin, Kwancheol Shin, Zhi Zhou:
Electrical Impedance Tomography with Deep Calderón Method. CoRR abs/2304.09074 (2023) - [i46]Siyu Cen, Bangti Jin, Yikan Liu, Zhi Zhou:
Recovery of Multiple Parameters in Subdiffusion from One Lateral Boundary Measurement. CoRR abs/2307.03263 (2023) - [i45]Bangti Jin, Jing Li, Yifeng Xu, Shengfeng Zhu:
An Adaptive Phase-Field Method for Structural Topology Optimization. CoRR abs/2308.06756 (2023) - [i44]Bangti Jin, Zehui Zhou, Jun Zou:
On the Approximation of Bi-Lipschitz Maps by Invertible Neural Networks. CoRR abs/2308.09367 (2023) - [i43]Bangti Jin, Ramesh Sau, Luowei Yin, Zhi Zhou:
Solving Elliptic Optimal Control Problems using Physics Informed Neural Networks. CoRR abs/2308.11925 (2023) - [i42]Imraj RD Singh, Alexander Denker, Riccardo Barbano, Zeljko Kereta, Bangti Jin, Kris Thielemans
Score-Based Generative Models for PET Image Reconstruction. CoRR abs/2308.14190 (2023) - [i41]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 abs/2308.14409 (2023) - [i40]Tianhao Hu, Bangti Jin, Zhi Zhou:
Solving Poisson Problems in Polygonal Domains with Singularity Enriched Physics Informed Neural Networks. CoRR abs/2308.16429 (2023) - [i39]Derick Nganyu Tanyu
Electrical Impedance Tomography: A Fair Comparative Study on Deep Learning and Analytic-based Approaches. CoRR abs/2310.18636 (2023) - [i38]Bangti Jin, Kwancheol Shin, Zhi Zhou:
Numerical Recovery of a Time-Dependent Potential in Subdiffusion. CoRR abs/2311.02420 (2023) - [i37]Junqing Chen, Bangti Jin, Haibo Liu:
Solving Inverse Obstacle Scattering Problem with Latent Surface Representations. CoRR abs/2311.07187 (2023) - [i36]Bangti Jin, Qingle Lin, Zhi Zhou:
Learning Coarse Propagators in Parareal Algorithm. CoRR abs/2311.15320 (2023) - 2022
- [j48]Bangti Jin, Yavar Kian
Recovery of the Order of Derivation for Fractional Diffusion Equations in an Unknown Medium. SIAM J. Appl. Math. 82(3): 1045-1067 (2022) - [j47]Huan Liu, Bangti Jin, Xiliang Lu:
Imaging Anisotropic Conductivities from Current Densities. SIAM J. Imaging Sci. 15(2): 860-891 (2022) - [j46]Riccardo Barbano
An Educated Warm Start for Deep Image Prior-Based Micro CT Reconstruction. IEEE Trans. Computational Imaging 8: 1210-1222 (2022) - [i35]Javier Antorán, Riccardo Barbano, Johannes Leuschner, José Miguel Hernández-Lobato, Bangti Jin:
A Probabilistic Deep Image Prior for Computational Tomography. CoRR abs/2203.00479 (2022) - [i34]Huan Liu, Bangti Jin, Xiliang Lu:
Imaging Anisotropic Conductivities from Current Densities. CoRR abs/2203.02164 (2022) - [i33]Bangti Jin, Xiliang Lu, Qimeng Quan, Zhi Zhou:
Convergence Rate Analysis of Galerkin Approximation of Inverse Potential Problem. CoRR abs/2203.04899 (2022) - [i32]Bangti Jin, Xiyao Li, Xiliang Lu:
Imaging Conductivity from Current Density Magnitude using Neural Networks. CoRR abs/2204.02441 (2022) - [i31]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 abs/2207.05714 (2022) - [i30]Bangti Jin, Yavar Kian:
Recovery of a Distributed Order Fractional Derivative in an Unknown Medium. CoRR abs/2207.12929 (2022) - [i29]Tianhao Hu, Bangti Jin, Zhi Zhou:
Solving Elliptic Problems with Singular Sources using Singularity Splitting Deep Ritz Method. CoRR abs/2209.02931 (2022) - [i28]Bangti Jin, Yavar Kian, Zhi Zhou:
Inverse Problems for Subdiffusion from Observation at an Unknown Terminal Time. CoRR abs/2210.07589 (2022) - 2021
- [j45]Chen Zhang, Riccardo Barbano, Bangti Jin
Conditional Variational Autoencoder for Learned Image Reconstruction. Comput. 9(11): 114 (2021) - [j44]Bangti Jin, Zehui Zhou
On the Saturation Phenomenon of Stochastic Gradient Descent for Linear Inverse Problems. SIAM/ASA J. Uncertain. Quantification 9(4): 1553-1588 (2021) - [j43]Bangti Jin, Zhi Zhou
Numerical Estimation of a Diffusion Coefficient in Subdiffusion. SIAM J. Control. Optim. 59(2): 1466-1496 (2021) - [j42]Bangti Jin, Yavar Kian
Reconstruction of a Space-Time-Dependent Source in Subdiffusion Models via a Perturbation Approach. SIAM J. Math. Anal. 53(4): 4445-4473 (2021) - [j41]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): 119-142 (2021) - [i27]Bangti Jin, Yavar Kian:
Recovery of the Order of Derivation for Fractional Diffusion Equations in an Unknown Medium. CoRR abs/2101.09165 (2021) - [i26]Bangti Jin, Yavar Kian, Zhi Zhou:
Reconstruction of a Space-Time Dependent Source in Subdiffusion Models via a Perturbation Approach. CoRR abs/2102.03041 (2021) - [i25]Bangti Jin, Zhi Zhou:
Recovering the Potential in One-Dimensional Time-Fractional Diffusion with Unknown Initial Condition and Source. CoRR abs/2105.14736 (2021) - [i24]Bangti Jin, Yavar Kian:
Recovering Multiple Fractional Orders in Time-Fractional Diffusion in an Unknown Medium. CoRR abs/2106.02554 (2021) - [i23]Zeljko Kereta, Robert Twyman, Simon R. Arridge, Kris Thielemans, Bangti Jin:
Stochastic EM methods with Variance Reduction for Penalised PET Reconstructions. CoRR abs/2106.03172 (2021) - [i22]Riccardo Barbano, Zeljko Kereta, Andreas Hauptmann, Simon R. Arridge, Bangti Jin:
Unsupervised Knowledge-Transfer for Learned Image Reconstruction. CoRR abs/2107.02572 (2021) - [i21]Bangti Jin, Zehui Zhou, Jun Zou:
An Analysis of Stochastic Variance Reduced Gradient for Linear Inverse Problems. CoRR abs/2108.04429 (2021) - [i20]Bangti Jin, Zhi Zhou:
Recovery of a Space-Time Dependent Diffusion Coefficient in Subdiffusion: Stability, Approximation and Error Analysis. CoRR abs/2109.06789 (2021) - [i19]Chen Zhang, Riccardo Barbano, Bangti Jin:
Conditional Variational Autoencoder for Learned Image Reconstruction. CoRR abs/2110.11681 (2021) - [i18]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 abs/2111.11926 (2021) - 2020
- [j40]Bangti Jin, Zhi Zhou
Incomplete iterative solution of subdiffusion. Numerische Mathematik 145(3): 693-725 (2020) - [j39]Bangti Jin, Buyang Li, Zhi Zhou
Subdiffusion with time-dependent coefficients: improved regularity and second-order time stepping. Numerische Mathematik 145(4): 883-913 (2020) - [j38]Bangti Jin, Zehui Zhou
On the Convergence of Stochastic Gradient Descent for Nonlinear Ill-Posed Problems. SIAM J. Optim. 30(2): 1421-1450 (2020) - [c2]Riccardo Barbano, Chen Zhang, Simon R. Arridge, Bangti Jin:
Quantifying Model Uncertainty in Inverse Problems via Bayesian Deep Gradient Descent. ICPR 2020: 1392-1399 - [i17]Tobias Kluth, Bangti Jin:
L1 data fitting for robust reconstruction in magnetic particle imaging: quantitative evaluation on Open MPI dataset. CoRR abs/2001.06083 (2020) - [i16]Bangti Jin, Buyang Li, Zhi Zhou:
Subdiffusion with Time-Dependent Coefficients: Improved Regularity and Second-Order Time Stepping. CoRR abs/2004.11151 (2020) - [i15]Tim Jahn, Bangti Jin:
On the Discrepancy Principle for Stochastic Gradient Descent. CoRR abs/2004.14625 (2020) - [i14]Riccardo Barbano, Chen Zhang, Simon R. Arridge, Bangti Jin:
Quantifying Model Uncertainty in Inverse Problems via Bayesian Deep Gradient Descent. CoRR abs/2007.09971 (2020) - [i13]Bangti Jin, Zhi Zhou:
An Inverse Potential Problem for Subdiffusion: Stability and Reconstruction. CoRR abs/2009.03516 (2020) - [i12]Bangti Jin, Zhi Zhou:
Error Analysis of Finite Element Approximations of Diffusion Coefficient Identification for Elliptic and Parabolic Problems. CoRR abs/2010.02447 (2020) - [i11]Bangti Jin, Zehui Zhou, Jun Zou:
On the Saturation Phenomenon of Stochastic Gradient Descent for Linear Inverse Problems. CoRR abs/2010.10916 (2020) - [i10]Riccardo Barbano, Zeljko Kereta, Chen Zhang, Andreas Hauptmann, Simon R. Arridge, Bangti Jin:
Quantifying Sources of Uncertainty in Deep Learning-Based Image Reconstruction. CoRR abs/2011.08413 (2020)
2010 – 2019
- 2019
- [j37]Bangti Jin, Buyang Li
Subdiffusion with a time-dependent coefficient: Analysis and numerical solution. Math. Comput. 88(319): 2157-2186 (2019) - [i9]Bangti Jin, Zhi Zhou:
Incomplete Iterative Solution of the Subdiffusion Problem. CoRR abs/1906.06497 (2019) - [i8]Bangti Jin, Zehui Zhou, Jun Zou:
On the Convergence of Stochastic Gradient Descent for Nonlinear Ill-Posed Problems. CoRR abs/1907.03132 (2019) - [i7]Manh Hong Duong, Bangti Jin:
Wasserstein Gradient Flow Formulation of the Time-Fractional Fokker-Planck Equation. CoRR abs/1908.09055 (2019) - [i6]Bangti Jin, Zhi Zhou:
Numerical Estimation of a Diffusion Coefficient in Subdiffusion. CoRR abs/1909.00334 (2019) - [i5]Kazufumi Ito, Bangti Jin:
Regularized Linear Inversion with Randomized Singular Value Decomposition. CoRR abs/1909.01947 (2019) - [i4]Federico Benvenuto, Bangti Jin:
A Parameter Choice Rule for Tikhonov Regularization Based on Predictive Risk. CoRR abs/1912.13004 (2019) - 2018
- [j36]Beiping Duan
Space-Time Petrov-Galerkin FEM for Fractional Diffusion Problems. Comput. Methods Appl. Math. 18(1): 1-20 (2018) - [j35]Bangti Jin, Buyang Li
Discrete maximal regularity of time-stepping schemes for fractional evolution equations. Numerische Mathematik 138(1): 101-131 (2018) - [j34]Bangti Jin, Buyang Li, Zhi Zhou
Numerical Analysis of Nonlinear Subdiffusion Equations. SIAM J. Numer. Anal. 56(1): 1-23 (2018) - 2017
- [j33]Bangti Jin, Raytcho D. Lazarov
Preface: Numerical Analysis of Fractional Differential Equations. Comput. Methods Appl. Math. 17(4): 643-646 (2017) - [j32]Bangti Jin, Raytcho D. Lazarov
On nonnegativity preservation in finite element methods for subdiffusion equations. Math. Comput. 86(307): 2239-2260 (2017) - [j31]Bangti Jin, Buyang Li
Correction of High-Order BDF Convolution Quadrature for Fractional Evolution Equations. SIAM J. Sci. Comput. 39(6) (2017) - [j30]Yuling Jiao
Iterative Soft/Hard Thresholding With Homotopy Continuation for Sparse Recovery. IEEE Signal Process. Lett. 24(6): 784-788 (2017) - [j29]Yuling Jiao
Group Sparse Recovery via the ℓ0(ℓ2) Penalty: Theory and Algorithm. IEEE Trans. Signal Process. 65(4): 998-1012 (2017) - 2016
- [j28]Bangti Jin, Raytcho D. Lazarov
A simple finite element method for boundary value problems with a Riemann-Liouville derivative. J. Comput. Appl. Math. 293: 94-111 (2016) - [j27]Giovanni S. Alberti
The Linearized Inverse Problem in Multifrequency Electrical Impedance Tomography. SIAM J. Imaging Sci. 9(4): 1525-1551 (2016) - [j26]Bangti Jin, Raytcho D. Lazarov
A Petrov-Galerkin Finite Element Method for Fractional Convection-Diffusion Equations. SIAM J. Numer. Anal. 54(1): 481-503 (2016) - [j25]Bangti Jin, Raytcho D. Lazarov
Two Fully Discrete Schemes for Fractional Diffusion and Diffusion-Wave Equations with Nonsmooth Data. SIAM J. Sci. Comput. 38(1) (2016) - [i3]Yuling Jiao, Bangti Jin, Xiliang Lu:
Group Sparse Recovery via the ℓ0(ℓ2) Penalty: Theory and Algorithm. CoRR abs/1601.04174 (2016) - 2015
- [j24]Zhiyuan Sun
Numerical identification of a sparse Robin coefficient. Adv. Comput. Math. 41(1): 131-148 (2015) - [j23]Kazufumi Ito, Bangti Jin, Tomoya Takeuchi:
On the sectorial property of the Caputo derivative operator. Appl. Math. Lett. 47: 43-46 (2015) - [j22]Bangti Jin, Raytcho D. Lazarov
The Galerkin finite element method for a multi-term time-fractional diffusion equation. J. Comput. Phys. 281: 825-843 (2015) - [j21]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: 377-393 (2015) - [j20]Bangti Jin, Raytcho D. Lazarov
Variational formulation of problems involving fractional order differential operators. Math. Comput. 84(296): 2665-2700 (2015) - [j19]Emilia G. Bazhlekova
An analysis of the Rayleigh-Stokes problem for a generalized second-grade fluid. Numerische Mathematik 131(1): 1-31 (2015) - 2014
- [j18]Matthias Gehre, Bangti Jin:
Expectation propagation for nonlinear inverse problems - with an application to electrical impedance tomography. J. Comput. Phys. 259: 513-535 (2014) - [j17]Bangti Jin, Raytcho D. Lazarov
Error Analysis of a Finite Element Method for the Space-Fractional Parabolic Equation. SIAM J. Numer. Anal. 52(5): 2272-2294 (2014) - [i2]Yuling Jiao, Bangti Jin, Xiliang Lu:
A Primal Dual Active Set with Continuation Algorithm for the \ell^0-Regularized Optimization Problem. CoRR abs/1403.0515 (2014) - 2013
- [j16]Victor M. Calo
Gradient-based estimation of Manning's friction coefficient from noisy data. J. Comput. Appl. Math. 238: 1-13 (2013) - [j15]Kazufumi Ito, Bangti Jin, Jun Zou:
A two-stage method for inverse medium scattering. J. Comput. Phys. 237: 211-223 (2013) - [j14]Bangti Jin, Raytcho D. Lazarov
Error Estimates for a Semidiscrete Finite Element Method for Fractional Order Parabolic Equations. SIAM J. Numer. Anal. 51(1): 445-466 (2013) - 2012
- [j13]Matthias Gehre, Tobias Kluth
Sparsity reconstruction in electrical impedance tomography: An experimental evaluation. J. Comput. Appl. Math. 236(8): 2126-2136 (2012) - [j12]Bangti Jin:
A variational Bayesian method to inverse problems with impulsive noise. J. Comput. Phys. 231(2): 423-435 (2012) - [j11]Bangti Jin, William Rundell:
An inverse Sturm-Liouville problem with a fractional derivative. J. Comput. Phys. 231(14): 4954-4966 (2012) - [j10]Bangti Jin, Xiliang Lu
Numerical identification of a Robin coefficient in parabolic problems. Math. Comput. 81(279): 1369-1398 (2012) - [j9]Christian Clason
A Semismooth Newton Method for Nonlinear Parameter Identification Problems with Impulsive Noise. SIAM J. Imaging Sci. 5(2): 505-536 (2012) - [c1]Bangti Jin, Raytcho D. Lazarov
Galerkin FEM for Fractional Order Parabolic Equations with Initial Data in H - s , 0 ≤ s ≤ 1. NAA 2012: 24-37 - 2011
- [j8]Kazufumi Ito, Bangti Jin, Tomoya Takeuchi:
A Regularization Parameter for Nonsmooth Tikhonov Regularization. SIAM J. Sci. Comput. 33(3): 1415-1438 (2011) - [i1]Kazufumi Ito, Bangti Jin, Tomoya Takeuchi:
Multi-Parameter Tikhonov Regularization. CoRR abs/1102.1173 (2011) - 2010
- [j7]Bangti Jin, Jun Zou:
Hierarchical Bayesian inference for Ill-posed problems via variational method. J. Comput. Phys. 229(19): 7317-7343 (2010) - [j6]Christian Clason
A Semismooth Newton Method for L1 Data Fitting with Automatic Choice of Regularization Parameters and Noise Calibration. SIAM J. Imaging Sci. 3(2): 199-231 (2010) - [j5]Bangti Jin, Dirk A. Lorenz
Heuristic Parameter-Choice Rules for Convex Variational Regularization Based on Error Estimates. SIAM J. Numer. Anal. 48(3): 1208-1229 (2010) - [j4]Christian Clason
A Duality-Based Splitting Method for l1-TV Image Restoration with Automatic Regularization Parameter Choice. SIAM J. Sci. Comput. 32(3): 1484-1505 (2010)
2000 – 2009
- 2009
- [j3]Bangti Jin, Jun Zou:
Numerical Estimation of Piecewise Constant Robin Coefficient. SIAM J. Control. Optim. 48(3): 1977-2002 (2009) - 2008
- [j2]Bangti Jin, Jun Zou:
Inversion of Robin coefficient by a spectral stochastic finite element approach. J. Comput. Phys. 227(6): 3282-3306 (2008) - 2006
- [j1]Bangti Jin, Wen Chen:
Boundary knot method based on geodesic distance for anisotropic problems. J. Comput. Phys. 215(2): 614-629 (2006)
Coauthor Index
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