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2020 – today
- 2025
[i16]Emma Hart, Julianne Chung, Matthias Chung:
A Paired Autoencoder Framework for Inverse Problems via Bayes Risk Minimization. CoRR abs/2501.14636 (2025)- 2024
- [i15]Matthias Chung, Emma Hart, Julianne Chung, Bas Peters, Eldad Haber:
Paired Autoencoders for Inverse Problems. CoRR abs/2405.13220 (2024) - [i14]Matthias Chung, Rick Archibald, Paul J. Atzberger, Jack Michael Solomon:
Sparse L1-Autoencoders for Scientific Data Compression. CoRR abs/2405.14270 (2024) - [i13]Cristina Sgattoni, Luca Sgheri, Matthias Chung:
A physics-aware data-driven surrogate approach for fast atmospheric radiative transfer inversion. CoRR abs/2410.22609 (2024) - [i12]Moritz Piening, Matthias Chung:
Paired Wasserstein Autoencoders for Conditional Sampling. CoRR abs/2412.07586 (2024) - 2023
- [j11]Matthias Chung
, Justin Krueger, Honghu Liu:
Least-squares finite element method for ordinary differential equations. J. Comput. Appl. Math. 418: 114660 (2023) - [j10]Rana A. Genedy, Matthias Chung, Jactone A. Ogejo:
Physics-informed neural networks for predicting liquid dairy manure temperature during storage. Neural Comput. Appl. 35(16): 12159-12174 (2023) - [i11]Babak Maboudi Afkham, Julianne Chung, Matthias Chung:
Goal-oriented Uncertainty Quantification for Inverse Problems via Variational Encoder-Decoder Networks. CoRR abs/2304.08324 (2023) - [i10]Elizabeth Newman, Jack Michael Solomon, Matthias Chung:
Image reconstructions using sparse dictionary representations and implicit, non-negative mappings. CoRR abs/2312.03180 (2023) - 2022
- [j9]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) - [i9]Matthias Chung, Rosemary Renaut:
The Variable Projected Augmented Lagrangian Method. CoRR abs/2207.08216 (2022) - 2021
- [i8]Babak Maboudi Afkham, Julianne Chung, Matthias Chung:
Learning Regularization Parameters of Inverse Problems via Deep Neural Networks. CoRR abs/2104.06594 (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]Matthias Chung, Justin Krueger, Honghu Liu:
Least-Squares Finite Element Method for Ordinary Differential Equations. CoRR abs/2109.15133 (2021) - [i5]Julianne Chung, Matthias Chung, Silvia Gazzola, Mirjeta Pasha:
Efficient learning methods for large-scale optimal inversion design. CoRR abs/2110.02720 (2021)
2010 – 2019
- 2019
- [j8]Matthias Chung, Mickaël Binois, Robert B. Gramacy, Johnathan M. Bardsley, David J. Moquin, Amanda P. Smith, Amber M. Smith:
Parameter and Uncertainty Estimation for Dynamical Systems Using Surrogate Stochastic Processes. SIAM J. Sci. Comput. 41(4): A2212-A2238 (2019) - [c3]Julianne Chung, Matthias Chung, J. Tanner Slagel:
Iterative Sampled Methods for Massive and Separable Nonlinear Inverse Problems. SSVM 2019: 119-130 - [i4]Julianne Chung, Matthias Chung, J. Tanner Slagel, Luis Tenorio:
Sampled Limited Memory Methods for Massive Linear Inverse Problems. CoRR abs/1912.07962 (2019) - 2018
- [j7]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
- [j6]Julianne Chung, Matthias Chung:
Optimal Regularized Inverse Matrices for Inverse Problems. SIAM J. Matrix Anal. Appl. 38(2): 458-477 (2017) - [i3]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) - 2016
- [c2]Robert J. Smith?, Bruce Y. Lee, Aristides Moustakas, Andreas Zeigler, Mélanie Prague, Romualdo Santos, Matthias Chung, Robin Gras, Valery Forbes, Sixten Borg, Tracy Comans, Yifei Ma, Nieko Punt, William Jusko, Lucas Brotz, Ayaz Hyder:
Population modelling by examples ii. SummerSim 2016: 51 - 2014
- [i2]Julianne Chung, Matthias Chung:
An Efficient Approach for Computing Optimal Low-Rank Regularized Inverse Matrices. CoRR abs/1404.1610 (2014) - [i1]Eldad Haber, Matthias Chung:
Simultaneous Source for non-uniform data variance and missing data. CoRR abs/1404.5254 (2014) - 2013
- [j5]Matthias Chung, Qi Long, Brent A. Johnson:
A tutorial on rank-based coefficient estimation for censored data in small- and large-scale problems. Stat. Comput. 23(5): 601-614 (2013) - [c1]Julianne Chung, Matthias Chung:
Computing optimal low-rank matrix approximations for image processing. ACSSC 2013: 670-674 - 2012
- [j4]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) - [j3]Matthias Chung, Eldad Haber:
Experimental Design for Biological Systems. SIAM J. Control. Optim. 50(1): 471-489 (2012) - [j2]Eldad Haber, Matthias Chung, Felix Herrmann:
An Effective Method for Parameter Estimation with PDE Constraints with Multiple Right-Hand Sides. SIAM J. Optim. 22(3): 739-757 (2012) - 2011
- [j1]Julianne Chung, Matthias Chung, Dianne P. O'Leary:
Designing Optimal Spectral Filters for Inverse Problems. SIAM J. Sci. Comput. 33(6): 3132-3152 (2011)
Coauthor Index
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