Julianne Chung

According to our database, Julianne Chung authored at least 36 papers between 2010 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Efficient iterative methods for hyperparameter estimation in large-scale linear inverse problems.

Khalil A Hall-Hooper, Arvind K. Saibaba, Julianne Chung, Scot M. Miller

Adv. Comput. Math., December, 2024

Hybrid Projection Methods for Solution Decomposition in Large-Scale Bayesian Inverse Problems.

Julianne Chung, Jiahua Jiang, Scot M. Miller, Arvind K. Saibaba

SIAM J. Sci. Comput., 2024

Computational Methods for Large-Scale Inverse Problems: A Survey on Hybrid Projection Methods.

Julianne Chung, Silvia Gazzola

SIAM Rev., 2024

Efficient hyperparameter estimation in Bayesian inverse problems using sample average approximation.

Julianne Chung, Scot M. Miller, Malena Sabate Landman, Arvind K. Saibaba

CoRR, 2024

Inexact Generalized Golub-Kahan Methods for Large-Scale Bayesian Inverse Problems.

Yutong Bu, Julianne Chung

CoRR, 2024

Inner Product Free Krylov Methods for Large-Scale Inverse Problems.

Ariana N. Brown, Julianne Chung, James G. Nagy, Malena Sabaté Landman

CoRR, 2024

Paired Autoencoders for Inverse Problems.

Matthias Chung, Emma Hart, Julianne Chung, Bas Peters, Eldad Haber

CoRR, 2024

Iterative Reconstruction Methods for Cosmological X-Ray Tomography.

Julianne Chung, Lucas Onisk, Yiran Wang

CoRR, 2024

2023

Flexible Krylov Methods for Group Sparsity Regularization.

Julianne Chung, Malena Sabaté Landman

CoRR, 2023

Goal-oriented Uncertainty Quantification for Inverse Problems via Variational Encoder-Decoder Networks.

Babak Maboudi Afkham, Julianne Chung, Matthias Chung

CoRR, 2023

2022

slimTrain - A Stochastic Approximation Method for Training Separable Deep Neural Networks.

Elizabeth Newman, Julianne Chung, Matthias Chung, Lars Ruthotto

SIAM J. Sci. Comput., August, 2022

2021

Hybrid Projection Methods with Recycling for Inverse Problems.

Jiahua Jiang, Julianne Chung, Eric de Sturler

SIAM J. Sci. Comput., 2021

Research in Inverse Problems and Training in Computational Science: A Reflection on the Importance of Community.

Julianne Chung

Comput. Sci. Eng., 2021

Efficient learning methods for large-scale optimal inversion design.

Julianne Chung, Matthias Chung, Silvia Gazzola, Mirjeta Pasha

CoRR, 2021

Learning Regularization Parameters of Inverse Problems via Deep Neural Networks.

Babak Maboudi Afkham, Julianne Chung, Matthias Chung

CoRR, 2021

2020

Efficient Krylov subspace methods for uncertainty quantification in large Bayesian linear inverse problems.

Arvind K. Saibaba, Julianne Chung, Katrina Petroske

Numer. Linear Algebra Appl., 2020

Hybrid Projection Methods for Large-scale Inverse Problems with Mixed Gaussian Priors.

Taewon Cho, Julianne Chung, Jiahua Jiang

CoRR, 2020

2019

Flexible Krylov Methods for ℓ_p Regularization.

Julianne Chung, Silvia Gazzola

SIAM J. Sci. Comput., 2019

Sampled Limited Memory Methods for Massive Linear Inverse Problems.

Julianne Chung, Matthias Chung, J. Tanner Slagel, Luis Tenorio

CoRR, 2019

Iterative Sampled Methods for Massive and Separable Nonlinear Inverse Problems.

Julianne Chung, Matthias Chung, J. Tanner Slagel

Proceedings of the Scale Space and Variational Methods in Computer Vision, 2019

2018

Optimal Experimental Design for Inverse Problems with State Constraints.

Lars Ruthotto, Julianne Chung, Matthias Chung

SIAM J. Sci. Comput., 2018

2017

Generalized Hybrid Iterative Methods for Large-Scale Bayesian Inverse Problems.

Julianne Chung, Arvind K. Saibaba

SIAM J. Sci. Comput., 2017

Optimal Regularized Inverse Matrices for Inverse Problems.

Julianne Chung, Matthias Chung

SIAM J. Matrix Anal. Appl., 2017

Motion Estimation and Correction in Photoacoustic Tomographic Reconstruction.

Julianne Chung, Linh Nguyen

SIAM J. Imaging Sci., 2017

Stochastic Newton and Quasi-Newton Methods for Large Linear Least-squares Problems.

Julianne Chung, Matthias Chung, J. Tanner Slagel, Luis Tenorio

CoRR, 2017

2015

Large-Scale Inverse Problems in Imaging.

Julianne Chung, Sarah Knepper, James G. Nagy

Proceedings of the Handbook of Mathematical Methods in Imaging, 2015

A Hybrid LSMR Algorithm for Large-Scale Tikhonov Regularization.

Julianne Chung, Katrina Palmer

SIAM J. Sci. Comput., 2015

A Framework for Regularization via Operator Approximation.

Julianne M. Chung, Misha E. Kilmer, Dianne P. O'Leary

SIAM J. Sci. Comput., 2015

2014

An Efficient Approach for Computing Optimal Low-Rank Regularized Inverse Matrices.

Julianne Chung, Matthias Chung

CoRR, 2014

2013

Computing optimal low-rank matrix approximations for image processing.

Julianne Chung, Matthias Chung

Proceedings of the 2013 Asilomar Conference on Signals, 2013

2012

Optimal Filters from Calibration Data for Image Deconvolution with Data Acquisition Error.

Julianne Chung, Matthias Chung, Dianne P. O'Leary

J. Math. Imaging Vis., 2012

2011

Windowed Spectral Regularization of Inverse Problems.

Julianne Chung, Glenn R. Easley, Dianne P. O'Leary

SIAM J. Sci. Comput., 2011

Designing Optimal Spectral Filters for Inverse Problems.

Julianne Chung, Matthias Chung, Dianne P. O'Leary

SIAM J. Sci. Comput., 2011

2010

An Efficient Iterative Approach for Large-Scale Separable Nonlinear Inverse Problems.

Julianne Chung, James G. Nagy

SIAM J. Sci. Comput., 2010

Numerical Algorithms for Polyenergetic Digital Breast Tomosynthesis Reconstruction.

Julianne Chung, James G. Nagy, Ioannis Sechopoulos

SIAM J. Imaging Sci., 2010

High-Performance Three-Dimensional Image Reconstruction for Molecular Structure Determination.

Julianne Chung, Philip Sternberg, Chao Yang

Int. J. High Perform. Comput. Appl., 2010