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ORCIDJulianne Chung
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2020 – today
- 2024
[j19]Julianne Chung
, Silvia Gazzola:
Computational Methods for Large-Scale Inverse Problems: A Survey on Hybrid Projection Methods. SIAM Rev. 66(2): 205-284 (2024)- [j18]Julianne Chung, Jiahua Jiang, Scot M. Miller, Arvind K. Saibaba:
Hybrid Projection Methods for Solution Decomposition in Large-Scale Bayesian Inverse Problems. SIAM J. Sci. Comput. 46(2): S97-S119 (2024) - [i16]Julianne Chung, Lucas Onisk, Yiran Wang:
Iterative Reconstruction Methods for Cosmological X-Ray Tomography. CoRR abs/2405.02073 (2024) - [i15]Matthias Chung, Emma Hart, Julianne Chung, Bas Peters, Eldad Haber:
Paired Autoencoders for Inverse Problems. CoRR abs/2405.13220 (2024) - [i14]Ariana N. Brown, Julianne Chung, James G. Nagy, Malena Sabaté Landman:
Inner Product Free Krylov Methods for Large-Scale Inverse Problems. CoRR abs/2409.05239 (2024) - 2023
- [i13]Babak Maboudi Afkham, Julianne Chung, Matthias Chung:
Goal-oriented Uncertainty Quantification for Inverse Problems via Variational Encoder-Decoder Networks. CoRR abs/2304.08324 (2023) - [i12]Julianne Chung, Malena Sabaté Landman:
Flexible Krylov Methods for Group Sparsity Regularization. CoRR abs/2306.08499 (2023) - [i11]Khalil A Hall-Hooper, Arvind K. Saibaba, Julianne Chung, Scot M. Miller:
Efficient iterative methods for hyperparameter estimation in large-scale linear inverse problems. CoRR abs/2311.15827 (2023) - 2022
- [j17]Elizabeth Newman, Julianne Chung, Matthias Chung, Lars Ruthotto:
slimTrain - A Stochastic Approximation Method for Training Separable Deep Neural Networks. SIAM J. Sci. Comput. 44(4): 2322- (2022) - [i10]Julianne Chung, Jiahua Jiang, Scot M. Miller, Arvind K. Saibaba:
Hybrid Projection Methods for Solution Decomposition in Large-scale Bayesian Inverse Problems. CoRR abs/2206.06664 (2022) - 2021
- [j16]Julianne Chung:
Research in Inverse Problems and Training in Computational Science: A Reflection on the Importance of Community. Comput. Sci. Eng. 23(6): 25-33 (2021) - [j15]Jiahua Jiang, Julianne Chung, Eric de Sturler:
Hybrid Projection Methods with Recycling for Inverse Problems. SIAM J. Sci. Comput. 43(5): S146-S172 (2021) - [i9]Babak Maboudi Afkham, Julianne Chung, Matthias Chung:
Learning Regularization Parameters of Inverse Problems via Deep Neural Networks. CoRR abs/2104.06594 (2021) - [i8]Julianne Chung, Silvia Gazzola:
Computational methods for large-scale inverse problems: a survey on hybrid projection methods. CoRR abs/2105.07221 (2021) - [i7]Elizabeth Newman, Julianne Chung, Matthias Chung, Lars Ruthotto:
slimTrain - A Stochastic Approximation Method for Training Separable Deep Neural Networks. CoRR abs/2109.14002 (2021) - [i6]Julianne Chung, Matthias Chung, Silvia Gazzola, Mirjeta Pasha:
Efficient learning methods for large-scale optimal inversion design. CoRR abs/2110.02720 (2021) - 2020
- [j14]Arvind K. Saibaba, Julianne Chung, Katrina Petroske:
Efficient Krylov subspace methods for uncertainty quantification in large Bayesian linear inverse problems. Numer. Linear Algebra Appl. 27(5) (2020) - [i5]Taewon Cho, Julianne Chung, Jiahua Jiang:
Hybrid Projection Methods for Large-scale Inverse Problems with Mixed Gaussian Priors. CoRR abs/2003.13766 (2020) - [i4]Julianne Chung, Eric de Sturler, Jiahua Jiang:
Hybrid Projection Methods with Recycling for Inverse Problems. CoRR abs/2007.00207 (2020)
2010 – 2019
- 2019
- [j13]Julianne Chung, Silvia Gazzola:
Flexible Krylov Methods for ℓp Regularization. SIAM J. Sci. Comput. 41(5): S149-S171 (2019) - [c2]Julianne Chung, Matthias Chung, J. Tanner Slagel:
Iterative Sampled Methods for Massive and Separable Nonlinear Inverse Problems. SSVM 2019: 119-130 - [i3]Julianne Chung, Matthias Chung, J. Tanner Slagel, Luis Tenorio:
Sampled Limited Memory Methods for Massive Linear Inverse Problems. CoRR abs/1912.07962 (2019) - 2018
- [j12]Lars Ruthotto, Julianne Chung, Matthias Chung:
Optimal Experimental Design for Inverse Problems with State Constraints. SIAM J. Sci. Comput. 40(4): B1080-B1100 (2018) - 2017
- [j11]Julianne Chung, Linh Nguyen:
Motion Estimation and Correction in Photoacoustic Tomographic Reconstruction. SIAM J. Imaging Sci. 10(1): 216-242 (2017) - [j10]Julianne Chung, Matthias Chung:
Optimal Regularized Inverse Matrices for Inverse Problems. SIAM J. Matrix Anal. Appl. 38(2): 458-477 (2017) - [j9]Julianne Chung, Arvind K. Saibaba:
Generalized Hybrid Iterative Methods for Large-Scale Bayesian Inverse Problems. SIAM J. Sci. Comput. 39(5) (2017) - [i2]Julianne Chung, Matthias Chung, J. Tanner Slagel, Luis Tenorio:
Stochastic Newton and Quasi-Newton Methods for Large Linear Least-squares Problems. CoRR abs/1702.07367 (2017) - 2015
- [j8]Julianne M. Chung, Misha E. Kilmer, Dianne P. O'Leary:
A Framework for Regularization via Operator Approximation. SIAM J. Sci. Comput. 37(2) (2015) - [j7]Julianne Chung, Katrina Palmer:
A Hybrid LSMR Algorithm for Large-Scale Tikhonov Regularization. SIAM J. Sci. Comput. 37(5) (2015) - [r1]Julianne Chung, Sarah Knepper, James G. Nagy:
Large-Scale Inverse Problems in Imaging. Handbook of Mathematical Methods in Imaging 2015: 47-90 - 2014
- [i1]Julianne Chung, Matthias Chung:
An Efficient Approach for Computing Optimal Low-Rank Regularized Inverse Matrices. CoRR abs/1404.1610 (2014) - 2013
- [c1]Julianne Chung, Matthias Chung:
Computing optimal low-rank matrix approximations for image processing. ACSSC 2013: 670-674 - 2012
- [j6]Julianne Chung, Matthias Chung, Dianne P. O'Leary:
Optimal Filters from Calibration Data for Image Deconvolution with Data Acquisition Error. J. Math. Imaging Vis. 44(3): 366-374 (2012) - 2011
- [j5]Julianne Chung, Matthias Chung, Dianne P. O'Leary:
Designing Optimal Spectral Filters for Inverse Problems. SIAM J. Sci. Comput. 33(6): 3132-3152 (2011) - [j4]Julianne Chung, Glenn R. Easley, Dianne P. O'Leary:
Windowed Spectral Regularization of Inverse Problems. SIAM J. Sci. Comput. 33(6): 3175-3200 (2011) - 2010
- [j3]Julianne Chung, Philip Sternberg, Chao Yang:
High-Performance Three-Dimensional Image Reconstruction for Molecular Structure Determination. Int. J. High Perform. Comput. Appl. 24(2): 117-135 (2010) - [j2]Julianne Chung, James G. Nagy, Ioannis Sechopoulos:
Numerical Algorithms for Polyenergetic Digital Breast Tomosynthesis Reconstruction. SIAM J. Imaging Sci. 3(1): 133-152 (2010) - [j1]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)
Coauthor Index
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last updated on 2024-10-10 22:13 CEST by the dblp team
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