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James G. Nagy
Person information
- affiliation: Emory University, Atlanta, GA, USA
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2020 – today
- 2024
- [i11]Ariana N. Brown, Malena Sabaté Landman, James G. Nagy:
H-CMRH: a novel inner product free hybrid Krylov method for large-scale inverse problems. CoRR abs/2401.06918 (2024) - 2023
- [j42]Davide Evangelista
, Elena Morotti
, Elena Loli Piccolomini
, James G. Nagy:
Ambiguity in Solving Imaging Inverse Problems with Deep-Learning-Based Operators. J. Imaging 9(7): 133 (2023) - [j41]Chang Meng, James G. Nagy
:
Numerical methods for CT reconstruction with unknown geometry parameters. Numer. Algorithms 92(1): 831-847 (2023) - [i10]Davide Evangelista, Elena Morotti, Elena Loli Piccolomini, James G. Nagy:
Ambiguity in solving imaging inverse problems with deep learning based operators. CoRR abs/2305.19774 (2023) - 2022
- [j40]Difeng Cai
, James G. Nagy
, Yuanzhe Xi
:
Fast Deterministic Approximation of Symmetric Indefinite Kernel Matrices with High Dimensional Datasets. SIAM J. Matrix Anal. Appl. 43(2): 1003-1028 (2022) - [i9]Davide Evangelista, James G. Nagy, Elena Morotti, Elena Loli Piccolomini:
To be or not to be stable, that is the question: understanding neural networks for inverse problems. CoRR abs/2211.13692 (2022) - 2021
- [j39]Chao Wang
, Min Tao, James G. Nagy
, Yifei Lou
:
Limited-Angle CT Reconstruction via the L1/L2 Minimization. SIAM J. Imaging Sci. 14(2): 749-777 (2021) - [j38]Silvia Gazzola
, James G. Nagy
, Malena Sabate Landman
:
Iteratively Reweighted FGMRES and FLSQR for Sparse Reconstruction. SIAM J. Sci. Comput. 43(5): S47-S69 (2021) - [i8]Chao Wang
, Min Tao, Chen-Nee Chuah, James G. Nagy, Yifei Lou:
Minimizing L1 over L2 norms on the gradient. CoRR abs/2101.00809 (2021) - [i7]Difeng Cai, James G. Nagy, Yuanzhe Xi:
Fast and stable deterministic approximation of general symmetric kernel matrices in high dimensions. CoRR abs/2102.05215 (2021) - 2020
- [j37]Blair J. Rossetti
, Steven A. Wilbert, Jessica L. Mark Welch, Gary G. Borisy, James G. Nagy:
Semi-blind sparse affine spectral unmixing of autofluorescence-contaminated micrographs. Bioinform. 36(3): 910-917 (2020) - [j36]Zixuan Chen, James G. Nagy
, Yuanzhe Xi
, Bo Yu:
Structured FISTA for image restoration. Numer. Linear Algebra Appl. 27(2) (2020) - [j35]Silvia Gazzola
, Chang Meng, James G. Nagy
:
Krylov Methods for Low-Rank Regularization. SIAM J. Matrix Anal. Appl. 41(4): 1477-1504 (2020) - [j34]James L. Herring
, James G. Nagy, Lars Ruthotto:
Gauss-Newton Optimization for Phase Recovery From the Bispectrum. IEEE Trans. Computational Imaging 6: 235-247 (2020) - [i6]Xiaotong Chen, James L. Herring, James G. Nagy, Yuanzhe Xi, Bo Yu:
An ADMM-LAP method for total variation blind deconvolution of adaptive optics retinal images. CoRR abs/2001.01053 (2020) - [i5]Chao Wang, Min Tao, James G. Nagy, Yifei Lou:
Limited-angle CT reconstruction via the L1/L2 minimization. CoRR abs/2006.00601 (2020) - [i4]Kelvin K. Kan, James G. Nagy, Lars Ruthotto:
Avoiding The Double Descent Phenomenon of Random Feature Models Using Hybrid Regularization. CoRR abs/2012.06667 (2020)
2010 – 2019
- 2019
- [j33]Silvia Gazzola
, Per Christian Hansen
, James G. Nagy
:
IR Tools: a MATLAB package of iterative regularization methods and large-scale test problems. Numer. Algorithms 81(3): 773-811 (2019) - [j32]Yunyi Hu, Martin S. Andersen
, James G. Nagy:
Spectral Computed Tomography with Linearization and Preconditioning. SIAM J. Sci. Comput. 41(5): S370-S389 (2019) - [i3]Silvia Gazzola, Chang Meng, James G. Nagy:
Krylov Methods for Low-Rank Regularization. CoRR abs/1910.10664 (2019) - [i2]Silvia Gazzola, Misha E. Kilmer, James G. Nagy, Oguz Semerci, Eric L. Miller:
An Inner-Outer Iterative Method for Edge Preservation in Image Restoration and Reconstruction. CoRR abs/1912.13103 (2019) - 2018
- [j31]Marie Kubínová
, James G. Nagy:
Robust regression for mixed Poisson-Gaussian model. Numer. Algorithms 79(3): 825-851 (2018) - [j30]Jianjun Zhang, James G. Nagy
:
An alternating direction method of multipliers for the solution of matrix equations arising in inverse problems. Numer. Linear Algebra Appl. 25(4) (2018) - [j29]Clarissa C. Garvey, Chang Meng, James G. Nagy:
Singular Value Decomposition Approximation via Kronecker Summations for Imaging Applications. SIAM J. Matrix Anal. Appl. 39(4): 1836-1857 (2018) - [c8]Huamei Chen, John M. Irvine, Zhonghai Wang, Genshe Chen, Erik Blasch, James G. Nagy:
Predicting Interpretability Loss in Thermal IR Imagery due to Compression. AIPR 2018: 1-6 - [c7]Koen Michielsen
, Christian Fedon
, James G. Nagy, Ioannis Sechopoulos
:
Dose reduction in breast CT by spectrum switching. IWBI 2018: 107180J - 2017
- [i1]James L. Herring, James G. Nagy, Lars Ruthotto:
LAP: a Linearize and Project Method for Solving Inverse Problems with Coupled Variables. CoRR abs/1705.09992 (2017) - 2016
- [c6]Marcin Malec, Tushar Khot, James G. Nagy, Erik Blask, Sriraam Natarajan:
Inductive Logic Programming Meets Relational Databases: Efficient Learning of Markov Logic Networks. ILP 2016: 14-26 - [p1]Erik Blasch, Riad I. Hammoud, Haibin Ling, Dan Shen, James G. Nagy, Genshe Chen:
Context-Based Fusion of Physical and Human Data for Level 5 Information Fusion. Context-Enhanced Information Fusion 2016: 479-505 - 2015
- [j28]James G. Nagy, Michael K. Ng:
Dedication to Robert J. Plemmons. Numer. Linear Algebra Appl. 22(5): 793-794 (2015) - [j27]Sebastian Berisha, James G. Nagy, Robert J. Plemmons:
Estimation of atmospheric PSF parameters for hyperspectral imaging. Numer. Linear Algebra Appl. 22(5): 795-813 (2015) - [j26]Sebastian Berisha, James G. Nagy, Robert J. Plemmons:
Deblurring and Sparse Unmixing of Hyperspectral Images Using Multiple Point Spread Functions. SIAM J. Sci. Comput. 37(5) (2015) - [c5]Erik Blasch, Haibin Ling, Dan Shen, Genshe Chen, Riad I. Hammoud, Arslan Basharat, Roddy Collins, Alex Aved, James G. Nagy:
Video-to-text information fusion evaluation for level 5 user refinement. FUSION 2015: 1993-2000 - [r1]Julianne Chung, Sarah Knepper, James G. Nagy:
Large-Scale Inverse Problems in Imaging. Handbook of Mathematical Methods in Imaging 2015: 47-90 - 2014
- [j25]Anastasia Cornelio, Elena Loli Piccolomini
, James G. Nagy:
Constrained numerical optimization methods for blind deconvolution. Numer. Algorithms 65(1): 23-42 (2014) - [j24]Silvia Gazzola
, James G. Nagy:
Generalized Arnoldi-Tikhonov Method for Sparse Reconstruction. SIAM J. Sci. Comput. 36(2) (2014) - [c4]Erik Blasch, James G. Nagy, Alex Aved, Eric K. Jones, William M. Pottenger, Arslan Basharat, Anthony Hoogs, Michael Schneider, Riad I. Hammoud, Genshe Chen, Dan Shen, Haibin Ling:
Context aided video-to-text information fusion. FUSION 2014: 1-8 - 2013
- [j23]Veronica Mejia Bustamante, James G. Nagy, Steve S. J. Feng, Ioannis Sechopoulos
:
Iterative Breast Tomosynthesis Image Reconstruction. SIAM J. Sci. Comput. 35(5) (2013) - [j22]Qing Chu, Stuart Jefferies, James G. Nagy:
Iterative Wavefront Reconstruction for Astronomical Imaging. SIAM J. Sci. Comput. 35(5) (2013) - 2012
- [j21]Ying-Wai (Daniel) Fan, James G. Nagy:
An efficient computational approach for multiframe blind deconvolution. J. Comput. Appl. Math. 236(8): 2112-2125 (2012) - 2011
- [j20]Johnathan M. Bardsley, Sarah Knepper, James G. Nagy:
Structured linear algebra problems in adaptive optics imaging. Adv. Comput. Math. 35(2-4): 103-117 (2011) - [j19]Yangbo Ye, Robert J. Plemmons, James G. Nagy, Qinian Jin
:
Modern Mathematics in Biomedical Imaging. Int. J. Biomed. Imaging 2011: 618972:1-618972:2 (2011) - 2010
- [j18]Julianne Chung
, James G. Nagy, Ioannis Sechopoulos
:
Numerical Algorithms for Polyenergetic Digital Breast Tomosynthesis Reconstruction. SIAM J. Imaging Sci. 3(1): 133-152 (2010) - [j17]Julianne Chung
, James G. Nagy:
An Efficient Iterative Approach for Large-Scale Separable Nonlinear Inverse Problems. SIAM J. Sci. Comput. 31(6): 4654-4674 (2010) - [j16]Piotr Wendykier, James G. Nagy:
Parallel Colt: A High-Performance Java Library for Scientific Computing and Image Processing. ACM Trans. Math. Softw. 37(3): 31:1-31:22 (2010)
2000 – 2009
- 2008
- [j15]Per Christian Hansen, James G. Nagy, Dianne P. O'Leary, Rodney Miller:
Deblurring Images: Matrices, Spectra and Filtering. J. Electronic Imaging 17(1): 019901 (2008) - [c3]Piotr Wendykier, James G. Nagy:
Large-Scale Image Deblurring in Java. ICCS (1) 2008: 721-730 - 2007
- [j14]Misha Elena Kilmer, James G. Nagy:
Kronecker product approximations for dense block Toeplitz-plus-Hankel matrices. Numer. Linear Algebra Appl. 14(8): 581-602 (2007) - [c2]Martin Welk
, James G. Nagy:
Variational Deconvolution of Multi-channel Images with Inequality Constraints. IbPRIA (1) 2007: 386-393 - 2006
- [j13]Johnathan M. Bardsley, James G. Nagy:
Covariance-Preconditioned Iterative Methods for Nonnegatively Constrained Astronomical Imaging. SIAM J. Matrix Anal. Appl. 27(4): 1184-1197 (2006) - [j12]James G. Nagy, Misha Elena Kilmer:
Kronecker product approximation for preconditioning in three-dimensional imaging applications. IEEE Trans. Image Process. 15(3): 604-613 (2006) - 2004
- [j11]James G. Nagy, Katrina Palmer, Lisa Perrone:
Iterative Methods for Image Deblurring: A Matlab Object-Oriented Approach. Numer. Algorithms 36(1): 73-93 (2004) - 2003
- [j10]James G. Nagy, Dianne P. O'Leary:
Image deblurring: I can see clearly now. Comput. Sci. Eng. 5(3): 82-84 (2003) - [j9]Dianne P. O'Leary, Yalin Evren Sagduyu, James G. Nagy:
Robot control: swinging like a pendulum. Comput. Sci. Eng. 5(4): 68-71 (2003) - [j8]James G. Nagy, Dianne P. O'Leary:
Partial solution to "Image deblurring: I can see clearly now". Comput. Sci. Eng. 5(4): 72-74 (2003) - [j7]James G. Nagy, Michael K. Ng
, Lisa Perrone:
Kronecker Product Approximations forImage Restoration with Reflexive Boundary Conditions. SIAM J. Matrix Anal. Appl. 25(3): 829-841 (2003) - 2000
- [j6]Julie Kamm, James G. Nagy:
Optimal Kronecker Product Approximation of Block Toeplitz Matrices. SIAM J. Matrix Anal. Appl. 22(1): 155-172 (2000)
1990 – 1999
- 1998
- [j5]James G. Nagy, Dianne P. O'Leary:
Restoring Images Degraded by Spatially Variant Blur. SIAM J. Sci. Comput. 19(4): 1063-1082 (1998) - 1996
- [j4]James G. Nagy, Robert J. Plemmons, Todd C. Torgersen:
Iterative image restoration using approximate inverse preconditioning. IEEE Trans. Image Process. 5(7): 1151-1162 (1996) - [c1]Julie Kamm, James G. Nagy:
Least Squares and Total Least Squares Methods in Image Restoration. WNAA 1996: 212-219 - 1994
- [j3]Martin Hanke, James G. Nagy:
Toeplitz approximate inverse preconditioner for banded Toeplitz matrices. Numer. Algorithms 7(2): 183-199 (1994) - [j2]Raymond H. Chan, James G. Nagy, Robert J. Plemmons:
Circulant Preconditioned Toeplitz Least Squares Iterations. SIAM J. Matrix Anal. Appl. 15(1): 80-97 (1994) - 1993
- [j1]James G. Nagy:
Fast Inverse QR Factorization for Toeplitz Matrices. SIAM J. Sci. Comput. 14(5): 1174-1193 (1993)
Coauthor Index
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last updated on 2024-07-31 20:45 CEST by the dblp team
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