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04/17/2023
Goal-oriented Uncertainty Quantification for Inverse Problems via Variational Encoder-Decoder Networks
In this work, we describe a new approach that uses variational encoder-d...
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07/17/2022
The Variable Projected Augmented Lagrangian Method
Inference by means of mathematical modeling from a collection of observa...
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10/06/2021
Efficient learning methods for large-scale optimal inversion design
In this work, we investigate various approaches that use learning from t...
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09/30/2021
Least-Squares Finite Element Method for Ordinary Differential Equations
We consider the least-squares finite element method (lsfem) for systems ...
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09/28/2021
slimTrain – A Stochastic Approximation Method for Training Separable Deep Neural Networks
Deep neural networks (DNNs) have shown their success as high-dimensional...
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04/14/2021
Learning Regularization Parameters of Inverse Problems via Deep Neural Networks
In this work, we describe a new approach that uses deep neural networks ...
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12/17/2019
Sampled Limited Memory Methods for Massive Linear Inverse Problems
In many modern imaging applications the desire to reconstruct high resol...
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02/23/2017
