Preprints

Elizabeth Newman, Julianne Chung, Matthias Chung, Lars Ruthotto (2021). slimTrain - A Stochastic Approximation Method for Training Separable Deep Neural Networks. arxiv.org.

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Kelvin Kan, James G Nagy, Lars Ruthotto (2020). Avoiding The Double Descent Phenomenon of Random Feature Models Using Hybrid Regularization. arXiv.org.

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Derek Onken, Lars Ruthotto (2020). Discretize-Optimize vs. Optimize-Discretize for Time-Series Regression and Continuous Normalizing Flows. arXiv.org.

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Eran Treister, Lars Ruthotto, Michal Sharoni, Sapir Zafrani, Eldad Haber (2018). Low-Cost Parameterizations of Deep Convolutional Neural Networks. arXiv.org.

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Eldad Haber, Felix Lucka, Lars Ruthotto (2018). Never look back - A modified EnKF method and its application to the training of neural networks without back propagation. arXiv.org.

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Jan Macdonald, Lars Ruthotto (2016). Efficient Numerical Optimization For Susceptibility Artifact Correction Of EPI-MRI. arXiv.org.

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Book Chapter

Lars Ruthotto, Jan Modersitzki (2014). Non-linear Image Registration. Handbook of Mathematical Methods in Imaging.

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Journal Articles

Elizabeth Newman, Lars Ruthotto (2022). hessQuik: Fast Hessian computation of composite functions. The Journal of Open Source Software.

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Derek Onken, Levon Nurbekyan, Xingjian Li, Samy Wu Fung, Stanley Osher, Lars Ruthotto (2022). A Neural Network Approach for High-Dimensional Optimal Control Applied to Multi-Agent Path Finding. IEEE Transactions on Control Systems Technology.

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Elizabeth Newman, Lars Ruthotto, Joseph Hart, Bart van Bloemen Waanders (2021). Train Like a (Var)Pro: Efficient Training of Neural Networks with Variable Projection. SIAM Journal on Mathematics of Data Science (SIMODS).

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Kelvin Kan, Samy Wu Fung, Lars Ruthotto (2021). PNKH-B: A Projected Newton-Krylov Method for Large-Scale Bound-Constrained Optimization. SIAM Journal on Scientific Computing (SISC).

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Lars Ruthotto, Eldad Haber (2021). An Introduction to Deep Generative Modeling. GAMM Mitteilungen.

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Lars Ruthotto (2021). New Bridges Between Deep Learning and Partial Differential Equations. SIAM News.

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Stefanie Günther, Lars Ruthotto, Jacob B Schroder, Eric C Cyr, Nicolas R Gauger (2020). Layer-Parallel Training of Deep Residual Neural Networks. SIAM Journal on Mathematics of Data Science.

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Jonathan Ephrath, Moshe Eliasof, Lars Ruthotto, Eldad Haber, Eran Treister (2020). LeanConvNets: Low-cost Yet Effective Convolutional Neural Networks. IEEE Journal of Selected Topics in Signal Processing.

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Lars Ruthotto, Stanley J Osher, Wuchen Li, Levon Nurbekyan, Samy Wu Fung (2020). A machine learning framework for solving high-dimensional mean field game and mean field control problems. Proceedings of the National Academy of Sciences.

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Samy Wu Fung, Sanna Tyrväinen, Lars Ruthotto, Eldad Haber (2020). ADMM-Softmax: an ADMM approach for multinomial logistic regression. ETNA - Electronic Transactions on Numerical Analysis.

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Lars Ruthotto, Eldad Haber (2020). Deep neural networks motivated by partial differential equations. Journal of Mathematical Imaging and Vision.

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James Lincoln Herring, James Nagy, Lars Ruthotto (2020). Gauss–Newton Optimization for Phase Recovery From the Bispectrum. IEEE Transactions on Computational Imaging.

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Karsten Tabelow, Evelyne Balteau, John Ashburner, Martina F Callaghan, Bogdan Draganski, Gunther Helms, Ferath Kherif, Tobias Leutritz, Antoine Lutti, Christophe Phillips, Enrico Reimer, Lars Ruthotto, Maryam Seif, Nikolaus Weiskopf, Gabriel Ziegler, Siawoosh Mohammadi (2019). hMRI - A toolbox for quantitative MRI in neuroscience and clinical research. NeuroImage.

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Samy Wu Fung, Lars Ruthotto (2019). A Multiscale Method for Model Order Reduction in PDE Parameter Estimation. Journal of Computational and Applied Mathematics.

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Samy Wu Fung, Lars Ruthotto (2019). An Uncertainty-Weighted Asynchronous ADMM Method for Parallel PDE Parameter Estimation. SIAM Journal on Scientific Computing.

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Lauri Mustonen, Xiangxi Gao, Asteroide Santana, Rebecca Mitchell, Ymir Vigfusson, Lars Ruthotto (2018). A Bayesian framework for molecular strain identification from mixed diagnostic samples. Inverse Problems.

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Lars Ruthotto, Julianne Chung, Matthias Chung (2018). Optimal Experimental Design for Inverse Problems with State Constraints. SIAM Journal on Scientific Computing.

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Andreas Mang, Lars Ruthotto (2017). A Lagrangian Gauss-Newton-Krylov Solver for Mass- and Intensity-Preserving Diffeomorphic Image Registration. SIAM Journal on Scientific Computing.

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Lars Ruthotto, Chen Greif, Jan Modersitzki (2017). A Stabilized Multigrid Solver for Hyperelastic Image Registration. Numerical Linear Algebra With Applications.

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Jan Macdonald, Lars Ruthotto (2017). Improved Susceptibility Artifact Correction of Echo Planar MRI using the Alternating Direction Method of Multipliers. Journal of Mathematical Imaging and Vision.

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Lars Ruthotto, Eran Treister, Eldad Haber (2017). jInv - a Flexible Julia Package for PDE Parameter Estimation. SIAM Journal on Scientific Computing.

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James L Herring, James G Nagy, Lars Ruthotto (2017). LAP: a Linearize and Project Method for Solving Inverse Problems with Coupled Variables. STSIP Special Issue on Harmonic Analysis and Inverse Problems.

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Claire Y Lin, Alessandro Veneziani, Lars Ruthotto (2017). Numerical Methods for Polyline-to-Point-Cloud Registration with Applications to Patient-Specific Stent Reconstruction. International Journal for Numerical Methods in Biomedical Engineering.

Eldad Haber, Lars Ruthotto (2017). Stable architectures for deep neural networks. Inverse Problems.

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J Chung, Lars Ruthotto (2016). Computational methods for image reconstruction. NMR in Biomedicine.

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Eldad Haber, Lars Ruthotto (2014). A multiscale finite volume method for Maxwell's equations at low frequencies. Geophysical Journal International.

Jennifer Fohring, Eldad Haber, Lars Ruthotto (2014). Geophysical Imaging of Fluid Flow in Porous Media. SIAM Journal on Scientific Computing.

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Siawoosh Mohammadi, Karsten Tabelow, Lars Ruthotto, Thorsten Feiweier, Jörg Polzehl, Nikolaus Weiskopf (2014). High-resolution diffusion kurtosis imaging at 3T enabled by advanced post-processing.. Frontiers in Neuroscience.

Martin Burger, Jan Modersitzki, Lars Ruthotto (2013). A Hyperelastic Regularization Energy for Image Registration. SIAM Journal on Scientific Computing.

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Lars Ruthotto, H Kugel, J Olesch, B Fischer, J Modersitzki, M Burger, C H Wolters (2012). Diffeomorphic susceptibility artifact correction of diffusion-weighted magnetic resonance images. Physics in Medicine and Biology.

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Fabian Gigengack, Lars Ruthotto, Martin Burger, Carsten H Wolters, Xiaoyi Jiang, Klaus P Schäfers (2012). Motion Correction in Dual Gated Cardiac PET Using Mass-Preserving Image Registration. IEEE Transactions on Medical Imaging.

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Peer-Reviewed Conference Proceedings

Kelvin Kan, François-Xavier Aubet, Tim Januschowski, Youngsuk Park, Konstantinos Benidis, Lars Ruthotto, Jan Gasthaus (2022). Multivariate Quantile Function Forecaster. 25th International Conference on Artificial Intelligence and Statistics (AISTATS).

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Derek Onken, Levon Nurbekyan, Xingjian Li, Samy Wu Fung, Stanley Osher, Lars Ruthotto (2020). A Neural Network Approach Applied to Multi-Agent Optimal Control. ECC 2021.

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Derek Onken, Samy Wu Fung, Xingjian Li, Lars Ruthotto (2020). OT-Flow: Fast and Accurate Continuous Normalizing Flows via Optimal Transport. AAAI 2021.

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Jonathan Ephrath, Lars Ruthotto, Eldad Haber, Eran Treister (2019). LeanResNet: A Low-cost yet Effective Convolutional Residual Networks. Workshop on On Device Learning at the 36th International Conference on Machine Learning.

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Eldad Haber, Keegan Lensink, Eran Treister, Lars Ruthotto (2019). IMEXnet: A Forward Stable Deep Neural Network. 36th International Conference on Machine Learning.

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Bo Chang, Lili Meng, Eldad Haber, Lars Ruthotto, David Begert, Elliot Holtham (2018). Reversible architectures for arbitrarily deep residual neural networks. Thirty-Second AAAI Conference on Artificial Intelligence.

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Eldad Haber, Lars Ruthotto, Elliot Holtham, Seong-Hwan Jun (2017). Learning across scales - A multiscale method for Convolution Neural Networks. Thirty-Second AAAI Conference on Artificial Intelligence.

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Maximilian März, Lars Ruthotto (2016). Combined Background Field Removal and Reconstruction for Quantitative Susceptibility Mapping. Bildverarbeitung für die Medizin.

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Lars Ruthotto, Siawoosh Mohammadi, Nikolaus Weiskopf (2014). A New Method for Joint Susceptibility Artefact Correction and Super-Resolution for dMRI. Proc SPIE.

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Constantin Heck, Lars Ruthotto, Jan Modersitzki, Benjamin Berkels (2014). Model-based parameter estimation in DCE-MRI without an Arterial Input Function. Bildverarbeitung für die Medizin.

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Lars Ruthotto, Siawoosh Mohammadi, Constantin Heck, Jan Modersitzki, Nikolaus Weiskopf (2013). Hyperelastic Susceptibility Artifact Correction of DTI in SPM. Bildverarbeitung für die Medizin.

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Lars Ruthotto, Fabian Gigengack, Martin Burger, Carsten H Wolters, Xiaoyi Jiang, Klaus P Schäfers, Jan Modersitzki (2012). A Simplified Pipeline for Motion Correction in Dual Gated Cardiac PET. Bildverarbeitung für die Medizin.

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Lars Ruthotto, Erlend Hodneland, Jan Modersitzki (2012). Registration of Dynamic Contrast Enhanced MRI with Local Rigidity Constraint. Workshop on Biomedical Image Registration.

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Janine Olesch, Lars Ruthotto, Harald Kugel, Stefan Skare, Bernd Fischer, Carsten H Wolters (2010). A variational approach for the correction of field-inhomogeneities in EPI sequences. Proc SPIE.

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