Julianne Chung

49 papers Misc 1Journal 46Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Latent Space Inference via Paired Autoencoders. CoRR Emma Hart, Bas Peters, Julianne Chung, Matthias Chung
2025	J	`jnl`	A Paired Autoencoder Framework for Inverse Problems via Bayes Risk Minimization. CoRR Emma Hart, Julianne Chung, Matthias Chung
2025	J	`jnl`	Efficient sampling approaches based on generalized Golub-Kahan methods for large-scale hierarchical Bayesian inverse problems. CoRR Elle Buser, Julianne Chung
2025	J	`jnl`	Iterative Reconstruction Methods for Cosmological X-Ray Tomography. SIAM J. Imaging Sci. Julianne Chung, Lucas Onisk, Yiran Wang
2025	J	`jnl`	Randomized Krylov methods for inverse problems. CoRR Julianne Chung, Silvia Gazzola
2025	J	`jnl`	Randomized and Inner-product Free Krylov Methods for Large-scale Inverse Problems. CoRR Malena Sabaté Landman, Ariana N. Brown, Julianne Chung, James G. Nagy
2025	J	`jnl`	Randomized and inner-product free Krylov methods for large-scale inverse problems. Numer. Algorithms Malena Sabaté Landman, Ariana N. Brown, Julianne Chung, James G. Nagy
2025	J	`jnl`	Reconstruction of the observable universe from the integrated Sachs-Wolfe effect. CoRR Julianne Chung, Yiran Wang
2024	J	`jnl`	Computational Methods for Large-Scale Inverse Problems: A Survey on Hybrid Projection Methods. SIAM Rev. Julianne Chung, Silvia Gazzola
2024	J	`jnl`	Efficient hyperparameter estimation in Bayesian inverse problems using sample average approximation. CoRR Julianne Chung, Scot M. Miller, Malena Sabate Landman, Arvind K. Saibaba
2024	J	`jnl`	Efficient iterative methods for hyperparameter estimation in large-scale linear inverse problems. Adv. Comput. Math. Khalil A Hall-Hooper, Arvind K. Saibaba, Julianne Chung, Scot M. Miller
2024	J	`jnl`	Hybrid Projection Methods for Solution Decomposition in Large-Scale Bayesian Inverse Problems. SIAM J. Sci. Comput. Julianne Chung, Jiahua Jiang, Scot M. Miller, Arvind K. Saibaba
2024	J	`jnl`	Inexact Generalized Golub-Kahan Methods for Large-Scale Bayesian Inverse Problems. CoRR Yutong Bu, Julianne Chung
2024	J	`jnl`	Inner Product Free Krylov Methods for Large-Scale Inverse Problems. CoRR Ariana N. Brown, Julianne Chung, James G. Nagy, Malena Sabaté Landman
2024	J	`jnl`	Iterative Reconstruction Methods for Cosmological X-Ray Tomography. CoRR Julianne Chung, Lucas Onisk, Yiran Wang
2024	J	`jnl`	Paired Autoencoders for Inverse Problems. CoRR Matthias Chung, Emma Hart, Julianne Chung, Bas Peters, Eldad Haber
2024	J	`jnl`	Paired autoencoders for likelihood-free estimation in inverse problems. Mach. Learn. Sci. Technol. Matthias Chung, Emma Hart, Julianne Chung, Bas Peters, Eldad Haber
2023	J	`jnl`	Efficient iterative methods for hyperparameter estimation in large-scale linear inverse problems. CoRR Khalil A Hall-Hooper, Arvind K. Saibaba, Julianne Chung, Scot M. Miller
2023	J	`jnl`	Flexible Krylov Methods for Group Sparsity Regularization. CoRR Julianne Chung, Malena Sabaté Landman
2023	J	`jnl`	Goal-oriented Uncertainty Quantification for Inverse Problems via Variational Encoder-Decoder Networks. CoRR Babak Maboudi Afkham, Julianne Chung, Matthias Chung
2022	J	`jnl`	Hybrid Projection Methods for Solution Decomposition in Large-scale Bayesian Inverse Problems. CoRR Julianne Chung, Jiahua Jiang, Scot M. Miller, Arvind K. Saibaba
2022	J	`jnl`	slimTrain - A Stochastic Approximation Method for Training Separable Deep Neural Networks. SIAM J. Sci. Comput. Elizabeth Newman, Julianne Chung, Matthias Chung, Lars Ruthotto
2021	J	`jnl`	Computational methods for large-scale inverse problems: a survey on hybrid projection methods. CoRR Julianne Chung, Silvia Gazzola
2021	J	`jnl`	Efficient learning methods for large-scale optimal inversion design. CoRR Julianne Chung, Matthias Chung, Silvia Gazzola, Mirjeta Pasha
2021	J	`jnl`	Hybrid Projection Methods with Recycling for Inverse Problems. SIAM J. Sci. Comput. Jiahua Jiang, Julianne Chung, Eric de Sturler
2021	J	`jnl`	Learning Regularization Parameters of Inverse Problems via Deep Neural Networks. CoRR Babak Maboudi Afkham, Julianne Chung, Matthias Chung
2021	J	`jnl`	Research in Inverse Problems and Training in Computational Science: A Reflection on the Importance of Community. Comput. Sci. Eng. Julianne Chung
2021	J	`jnl`	slimTrain - A Stochastic Approximation Method for Training Separable Deep Neural Networks. CoRR Elizabeth Newman, Julianne Chung, Matthias Chung, Lars Ruthotto
2020	J	`jnl`	Efficient Krylov subspace methods for uncertainty quantification in large Bayesian linear inverse problems. Numer. Linear Algebra Appl. Arvind K. Saibaba, Julianne Chung, Katrina Petroske
2020	J	`jnl`	Hybrid Projection Methods for Large-scale Inverse Problems with Mixed Gaussian Priors. CoRR Taewon Cho, Julianne Chung, Jiahua Jiang
2020	J	`jnl`	Hybrid Projection Methods with Recycling for Inverse Problems. CoRR Julianne Chung, Eric de Sturler, Jiahua Jiang
2019	J	`jnl`	Flexible Krylov Methods for ℓ SIAM J. Sci. Comput. Julianne Chung, Silvia Gazzola
2019	—	`conf`	Iterative Sampled Methods for Massive and Separable Nonlinear Inverse Problems. SSVM Julianne Chung, Matthias Chung, J. Tanner Slagel
2019	J	`jnl`	Sampled Limited Memory Methods for Massive Linear Inverse Problems. CoRR Julianne Chung, Matthias Chung, J. Tanner Slagel, Luis Tenorio
2018	J	`jnl`	Optimal Experimental Design for Inverse Problems with State Constraints. SIAM J. Sci. Comput. Lars Ruthotto, Julianne Chung, Matthias Chung
2017	J	`jnl`	Generalized Hybrid Iterative Methods for Large-Scale Bayesian Inverse Problems. SIAM J. Sci. Comput. Julianne Chung, Arvind K. Saibaba
2017	J	`jnl`	Motion Estimation and Correction in Photoacoustic Tomographic Reconstruction. SIAM J. Imaging Sci. Julianne Chung, Linh Nguyen
2017	J	`jnl`	Optimal Regularized Inverse Matrices for Inverse Problems. SIAM J. Matrix Anal. Appl. Julianne Chung, Matthias Chung
2017	J	`jnl`	Stochastic Newton and Quasi-Newton Methods for Large Linear Least-squares Problems. CoRR Julianne Chung, Matthias Chung, J. Tanner Slagel, Luis Tenorio
2015	J	`jnl`	A Hybrid LSMR Algorithm for Large-Scale Tikhonov Regularization. SIAM J. Sci. Comput. Julianne Chung, Katrina Palmer
2015	—	`ch.`	Large-Scale Inverse Problems in Imaging. Handbook of Mathematical Methods in Imaging Julianne Chung, Sarah Knepper, James G. Nagy
2014	J	`jnl`	An Efficient Approach for Computing Optimal Low-Rank Regularized Inverse Matrices. CoRR Julianne Chung, Matthias Chung
2013	Misc	`conf`	Computing optimal low-rank matrix approximations for image processing. ACSSC Julianne Chung, Matthias Chung
2012	J	`jnl`	Optimal Filters from Calibration Data for Image Deconvolution with Data Acquisition Error. J. Math. Imaging Vis. Julianne Chung, Matthias Chung, Dianne P. O'Leary
2011	J	`jnl`	Designing Optimal Spectral Filters for Inverse Problems. SIAM J. Sci. Comput. Julianne Chung, Matthias Chung, Dianne P. O'Leary
2011	J	`jnl`	Windowed Spectral Regularization of Inverse Problems. SIAM J. Sci. Comput. Julianne Chung, Glenn R. Easley, Dianne P. O'Leary
2010	J	`jnl`	An Efficient Iterative Approach for Large-Scale Separable Nonlinear Inverse Problems. SIAM J. Sci. Comput. Julianne Chung, James G. Nagy
2010	J	`jnl`	High-Performance Three-Dimensional Image Reconstruction for Molecular Structure Determination. Int. J. High Perform. Comput. Appl. Julianne Chung, Philip Sternberg, Chao Yang
2010	J	`jnl`	Numerical Algorithms for Polyenergetic Digital Breast Tomosynthesis Reconstruction. SIAM J. Imaging Sci. Julianne Chung, James G. Nagy, Ioannis Sechopoulos