397 citations · 968 across the 32 of their papers we have counts for
7 papers · 1 filter
Reversible Architectures for Arbitrarily Deep Residual Neural Networks
Bo Chang, Lili Meng, Eldad Haber +3
Recently, deep residual networks have been successfully applied in many computer vision and natural language processing tasks, pushing the state-of-the-art performance with deeper…
Optimal Experimental Design for Constrained Inverse Problems
Lars Ruthotto, Julianne Chung, Matthias Chung
In this paper, we address the challenging problem of optimal experimental design (OED) of constrained inverse problems. We consider two OED formulations that allow reducing the exp…
A Multiscale Method for Model Order Reduction in PDE Parameter Estimation
Samy Wu Fung, Lars Ruthotto
Estimating parameters of Partial Differential Equations (PDEs) is of interest in a number of applications such as geophysical and medical imaging. Parameter estimation is commonly…
LAP: a Linearize and Project Method for Solving Inverse Problems with Coupled Variables
James Herring, James Nagy, Lars Ruthotto
Many inverse problems involve two or more sets of variables that represent different physical quantities but are tightly coupled with each other. For example, image super-resolutio…
Stable Architectures for Deep Neural Networks
Eldad Haber, Lars Ruthotto
Deep neural networks have become invaluable tools for supervised machine learning, e.g., classification of text or images. While often offering superior results over traditional te…
A Lagrangian Gauss-Newton-Krylov Solver for Mass- and Intensity-Preserving Diffeomorphic Image Registration
Andreas Mang, Lars Ruthotto
We present an efficient solver for diffeomorphic image registration problems in the framework of Large Deformations Diffeomorphic Metric Mappings (LDDMM). We use an optimal control…