Lars Ruthotto - RankMe

77 papers A* 5A 1B 2Journal 60Unranked 7

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Differentiating through Stochastic Differential Equations: A Primer. CoRR Rishi Leburu, Levon Nurbekyan, Lars Ruthotto
2026	J	`jnl`	Manifold-Aware Perturbations for Constrained Generative Modeling. CoRR Katherine Keegan, Lars Ruthotto
2025	J	`jnl`	Efficient Neural Network Approaches for Conditional Optimal Transport with Applications in Bayesian Inference. SIAM J. Sci. Comput. Zheyu Oliver Wang, Ricardo Baptista, Youssef Marzouk, Lars Ruthotto, Deepanshu Verma
2025	J	`jnl`	Mixed Precision Training of Neural ODEs. CoRR Elena Celledoni, Brynjulf Owren, Lars Ruthotto, Nicole Tianjiao Yang
2025	J	`jnl`	Multilevel Diffusion: Infinite Dimensional Score-Based Diffusion Models for Image Generation. SIAM J. Math. Data Sci. Paul Hagemann, Sophie Mildenberger, Lars Ruthotto, Gabriele Steidl, Nicole Tianjiao Yang
2025	J	`jnl`	The Future of Artificial Intelligence and the Mathematical and Physical Sciences (AI+MPS). CoRR Andrew Ferguson, Marisa Lafleur, Lars Ruthotto, Jesse Thaler, Yuan-Sen Ting, Pratyush Tiwary, Soledad Villar, E. Paulo Alves, Jeremy Avigad, Simon Billinge, Camille L. Bilodeau, Keith Brown, Emmanuel J. Candès, Arghya Chattopadhyay, Bingqing Cheng, Jonathan Clausen, Connor W. Coley, Andrew J. Connolly, Fred Daum, Sijia S. Dong, Chrisy Xiyu Du, Cora Dvorkin, Cristiano Fanelli, Eric B. Ford, Luis Manuel Frutos, Nicolás García Trillos, Cecilia Garraffo, Robert Ghrist, Rafael Gómez-Bombarelli, Gianluca Guadagni, Sreelekha Guggilam, Sergei Gukov, Juan B. Gutierrez, Salman Habib, Johannes Hachmann, Boris Hanin, Philip C. Harris, Murray Holland, Elizabeth Holm, Hsin-Yuan Huang, Shih-Chieh Hsu, Nick Jackson, Olexandr Isayev, Heng Ji, Aggelos K. Katsaggelos, Jeremy Kepner, Yannis G. Kevrekidis, Michelle P. Kuchera, J. Nathan Kutz, Branislava Lalic, Ann Lee, Matt LeBlanc, Josiah Lim, Rebecca Lindsey, Yongmin Liu, Peter Y. Lu, Sudhir Malik, Vuk Mandic, Vidya B. Manian, Emeka P. Mazi, Pankaj Mehta, Peter Melchior, Brice Ménard, Jennifer Ngadiuba, Stella Offner, Elsa Olivetti, Shyue Ping Ong, Christopher Rackauckas, Philippe Rigollet, Chad Risko, Philip Romero, Grant M. Rotskoff, Brett Savoie, Uros Seljak, David Shih, Gary Shiu, Dima Shlyakhtenko, Eva Silverstein, Taylor Sparks, Thomas Strohmer, Christopher Stubbs, Stephen Thomas, Suriyanarayanan Vaikuntanathan, René Vidal, Francisco Villaescusa-Navarro, Gregory Voth, Benjamin Wandelt, Rachel Ward, Melanie Weber, Risa Wechsler, Stephen Whitelam, Olaf Wiest, Mike Williams, Zhuoran Yang, Yaroslava G. Yingling, Bin Yu, Shuwen Yue, Ann Zabludoff, Huimin Zhao, Tong Zhang
2025	J	`jnl`	Weight-Parameterization in Continuous Time Deep Neural Networks for Surrogate Modeling. CoRR Haley Rosso, Lars Ruthotto, Khachik Sargsyan
2024	J	`jnl`	A Neural Network Approach for Stochastic Optimal Control. SIAM J. Sci. Comput. Xingjian Li, Deepanshu Verma, Lars Ruthotto
2024	J	`jnl`	Differential Equations for Continuous-Time Deep Learning. CoRR Lars Ruthotto
2024	J	`jnl`	PyHySCO: GPU-Enabled Susceptibility Artifact Distortion Correction in Seconds. CoRR Abigail Julian, Lars Ruthotto
2023	J	`jnl`	A Neural Network Approach for High-Dimensional Optimal Control Applied to Multiagent Path Finding. IEEE Trans. Control. Syst. Technol. Derek Onken, Levon Nurbekyan, Xingjian Li, Samy Wu Fung, Stanley J. Osher, Lars Ruthotto
2023	J	`jnl`	Alternating Minimization for Regression with Tropical Rational Functions. CoRR Alex Dunbar, Lars Ruthotto
2023	J	`jnl`	Efficient Neural Network Approaches for Conditional Optimal Transport with Applications in Bayesian Inference. CoRR Zheyu Oliver Wang, Ricardo Baptista, Youssef M. Marzouk, Lars Ruthotto, Deepanshu Verma
2023	A*	`conf`	Improving Graph Neural Networks with Learnable Propagation Operators. ICML Moshe Eliasof, Lars Ruthotto, Eran Treister
2023	J	`jnl`	Learning Control Policies of Hodgkin-Huxley Neuronal Dynamics. CoRR Malvern Madondo, Deepanshu Verma, Lars Ruthotto, Nicholas Au Yong
2023	J	`jnl`	MGIC: Multigrid-in-Channels Neural Network Architectures. SIAM J. Sci. Comput. Moshe Eliasof, Jonathan Ephrath, Lars Ruthotto, Eran Treister
2023	J	`jnl`	Multilevel Diffusion: Infinite Dimensional Score-Based Diffusion Models for Image Generation. CoRR Paul Hagemann, Lars Ruthotto, Gabriele Steidl, Nicole Tianjiao Yang
2022	J	`jnl`	'hessQuik': Fast Hessian computation of composite functions. J. Open Source Softw. Elizabeth Newman, Lars Ruthotto
2022	A	`conf`	Multivariate Quantile Function Forecaster. AISTATS Kelvin Kan, François-Xavier Aubet, Tim Januschowski, Youngsuk Park, Konstantinos Benidis, Lars Ruthotto, Jan Gasthaus
2022	J	`jnl`	Multivariate Quantile Function Forecaster. CoRR Kelvin Kan, François-Xavier Aubet, Tim Januschowski, Youngsuk Park, Konstantinos Benidis, Lars Ruthotto, Jan Gasthaus
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
2022	J	`jnl`	ωGNNs: Deep Graph Neural Networks Enhanced by Multiple Propagation Operators. CoRR Moshe Eliasof, Lars Ruthotto, Eran Treister
2021	—	`conf`	A Neural Network Approach Applied to Multi-Agent Optimal Control. ECC Derek Onken, Levon Nurbekyan, Xingjian Li, Samy Wu Fung, Stanley J. Osher, Lars Ruthotto
2021	J	`jnl`	An Introduction to Deep Generative Modeling. CoRR Lars Ruthotto, Eldad Haber
2021	A*	`conf`	OT-Flow: Fast and Accurate Continuous Normalizing Flows via Optimal Transport. AAAI Derek Onken, Samy Wu Fung, Xingjian Li, Lars Ruthotto
2021	J	`jnl`	PNKH-B: A Projected Newton-Krylov Method for Large-Scale Bound-Constrained Optimization. SIAM J. Sci. Comput. Kelvin K. Kan, Samy Wu Fung, Lars Ruthotto
2021	J	`jnl`	Train Like a (Var)Pro: Efficient Training of Neural Networks with Variable Projection. SIAM J. Math. Data Sci. Elizabeth Newman, Lars Ruthotto, Joseph L. Hart, Bart G. van Bloemen Waanders
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`	Avoiding The Double Descent Phenomenon of Random Feature Models Using Hybrid Regularization. CoRR Kelvin K. Kan, James G. Nagy, Lars Ruthotto
2020	J	`jnl`	Deep Neural Networks Motivated by Partial Differential Equations. J. Math. Imaging Vis. Lars Ruthotto, Eldad Haber
2020	J	`jnl`	Discretize-Optimize vs. Optimize-Discretize for Time-Series Regression and Continuous Normalizing Flows. CoRR Derek Onken, Lars Ruthotto
2020	J	`jnl`	Gauss-Newton Optimization for Phase Recovery From the Bispectrum. IEEE Trans. Computational Imaging James L. Herring, James G. Nagy, Lars Ruthotto
2020	J	`jnl`	Layer-Parallel Training of Deep Residual Neural Networks. SIAM J. Math. Data Sci. Stefanie Günther, Lars Ruthotto, Jacob B. Schroder, Eric C. Cyr, Nicolas R. Gauger
2020	J	`jnl`	LeanConvNets: Low-Cost Yet Effective Convolutional Neural Networks. IEEE J. Sel. Top. Signal Process. Jonathan Ephrath, Moshe Eliasof, Lars Ruthotto, Eldad Haber, Eran Treister
2020	J	`jnl`	Multigrid-in-Channels Neural Network Architectures. CoRR Moshe Eliasof, Jonathan Ephrath, Lars Ruthotto, Eran Treister
2020	J	`jnl`	OT-Flow: Fast and Accurate Continuous Normalizing Flows via Optimal Transport. CoRR Derek Onken, Samy Wu Fung, Xingjian Li, Lars Ruthotto
2020	J	`jnl`	PNKH-B: A Projected Newton-Krylov Method for Large-Scale Bound-Constrained Optimization. CoRR Kelvin K. Kan, Samy Wu Fung, Lars Ruthotto
2020	J	`jnl`	Train Like a (Var)Pro: Efficient Training of Neural Networks with Variable Projection. CoRR Elizabeth Newman, Lars Ruthotto, Joseph L. Hart, Bart G. van Bloemen Waanders
2019	J	`jnl`	A Machine Learning Framework for Solving High-Dimensional Mean Field Game and Mean Field Control Problems. CoRR Lars Ruthotto, Stanley J. Osher, Wuchen Li, Levon Nurbekyan, Samy Wu Fung
2019	J	`jnl`	A multiscale method for model order reduction in PDE parameter estimation. J. Comput. Appl. Math. Samy Wu Fung, Lars Ruthotto
2019	J	`jnl`	An Uncertainty-Weighted Asynchronous ADMM Method for Parallel PDE Parameter Estimation. SIAM J. Sci. Comput. Samy Wu Fung, Lars Ruthotto
2019	A*	`conf`	IMEXnet A Forward Stable Deep Neural Network. ICML Eldad Haber, Keegan Lensink, Eran Treister, Lars Ruthotto
2019	J	`jnl`	IMEXnet: A Forward Stable Deep Neural Network. CoRR Eldad Haber, Keegan Lensink, Eran Treister, Lars Ruthotto
2019	J	`jnl`	Large-Scale Classification using Multinomial Regression and ADMM. CoRR Samy Wu Fung, Sanna Tyrväinen, Lars Ruthotto, Eldad Haber
2019	J	`jnl`	LeanConvNets: Low-cost Yet Effective Convolutional Neural Networks. CoRR Jonathan Ephrath, Moshe Eliasof, Lars Ruthotto, Eldad Haber, Eran Treister
2019	J	`jnl`	LeanResNet: A Low-cost yet Effective Convolutional Residual Networks. CoRR Jonathan Ephrath, Lars Ruthotto, Eldad Haber, Eran Treister
2019	J	`jnl`	hMRI - A toolbox for quantitative MRI in neuroscience and clinical research. NeuroImage 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
2018	J	`jnl`	Deep Neural Networks motivated by Partial Differential Equations. CoRR Lars Ruthotto, Eldad Haber
2018	J	`jnl`	Improved Susceptibility Artifact Correction of Echo-Planar MRI using the Alternating Direction Method of Multipliers. J. Math. Imaging Vis. Jan MacDonald, Lars Ruthotto
2018	J	`jnl`	Layer-Parallel Training of Deep Residual Neural Networks. CoRR Stefanie Günther, Lars Ruthotto, Jacob B. Schroder, Eric C. Cyr, Nicolas R. Gauger
2018	A*	`conf`	Learning Across Scales - Multiscale Methods for Convolution Neural Networks. AAAI Eldad Haber, Lars Ruthotto, Elliot Holtham, Seong-Hwan Jun
2018	J	`jnl`	Low-Cost Parameterizations of Deep Convolution Neural Networks. CoRR Eran Treister, Lars Ruthotto, Michal Sharoni, Sapir Zafrani, Eldad Haber
2018	J	`jnl`	Never look back - A modified EnKF method and its application to the training of neural networks without back propagation. CoRR Eldad Haber, Felix Lucka, Lars Ruthotto
2018	J	`jnl`	Optimal Experimental Design for Inverse Problems with State Constraints. SIAM J. Sci. Comput. Lars Ruthotto, Julianne Chung, Matthias Chung
2018	A*	`conf`	Reversible Architectures for Arbitrarily Deep Residual Neural Networks. AAAI Bo Chang, Lili Meng, Eldad Haber, Lars Ruthotto, David Begert, Elliot Holtham
2017	J	`jnl`	A Lagrangian Gauss-Newton-Krylov Solver for Mass- and Intensity-Preserving Diffeomorphic Image Registration. CoRR Andreas Mang, Lars Ruthotto
2017	J	`jnl`	A Lagrangian Gauss-Newton-Krylov Solver for Mass- and Intensity-Preserving Diffeomorphic Image Registration. SIAM J. Sci. Comput. Andreas Mang, Lars Ruthotto
2017	J	`jnl`	A stabilized multigrid solver for hyperelastic image registration. Numer. Linear Algebra Appl. Lars Ruthotto, Chen Greif, Jan Modersitzki
2017	J	`jnl`	LAP: a Linearize and Project Method for Solving Inverse Problems with Coupled Variables. CoRR James L. Herring, James G. Nagy, Lars Ruthotto
2017	J	`jnl`	Learning across scales - A multiscale method for Convolution Neural Networks. CoRR Eldad Haber, Lars Ruthotto, Elliot Holtham
2017	J	`jnl`	Reversible Architectures for Arbitrarily Deep Residual Neural Networks. CoRR Bo Chang, Lili Meng, Eldad Haber, Lars Ruthotto, David Begert, Elliot Holtham
2017	J	`jnl`	Stable Architectures for Deep Neural Networks. CoRR Eldad Haber, Lars Ruthotto
2017	J	`jnl`	jInv-a Flexible Julia Package for PDE Parameter Estimation. SIAM J. Sci. Comput. Lars Ruthotto, Eran Treister, Eldad Haber
2016	—	`conf`	Combined Background Field Removal and Reconstruction for Quantitative Susceptibility Mapping. Bildverarbeitung für die Medizin Maximilian März, Lars Ruthotto
2016	J	`jnl`	jInv - a flexible Julia package for PDE parameter estimation. CoRR Lars Ruthotto, Eran Treister, Eldad Haber
2015	—	`ch.`	Non-linear Image Registration. Handbook of Mathematical Methods in Imaging Lars Ruthotto, Jan Modersitzki
2014	B	`conf`	A new method for joint susceptibility artefact correction and super-resolution for dMRI. Image Processing Lars Ruthotto, Siawoosh Mohammadi, Nikolaus Weiskopf
2014	J	`jnl`	Geophysical Imaging of Fluid Flow in Porous Media. SIAM J. Sci. Comput. Jennifer Fohring, Eldad Haber, Lars Ruthotto
2014	—	`conf`	Model-Based Parameterestimation in DCE-MRI Without an Arterial Input Function. Bildverarbeitung für die Medizin Constantin Heck, Lars Ruthotto, Jan Modersitzki, Benjamin Berkels
2013	J	`jnl`	A Hyperelastic Regularization Energy for Image Registration. SIAM J. Sci. Comput. Martin Burger, Jan Modersitzki, Lars Ruthotto
2013	—	`conf`	Hyperelastic Susceptibility Artifact Correction of DTI in SPM. Bildverarbeitung für die Medizin Lars Ruthotto, Siawoosh Mohammadi, Constantin Heck, Jan Modersitzki, Nikolaus Weiskopf
2012	—	`conf`	A Simplified Pipeline for Motion Correction in Dual Gated Cardiac PET. Bildverarbeitung für die Medizin Lars Ruthotto, Fabian Gigengack, Martin Burger, Carsten H. Wolters, Xiaoyi Jiang, Klaus P. Schäfers, Jan Modersitzki
2012	—	`conf`	Atlas-Based Whole-Body PET-CT Segmentation Using a Passive Contour Distance. MCV Fabian Gigengack, Lars Ruthotto, Xiaoyi Jiang, Jan Modersitzki, Martin Burger, Sven Hermann, Klaus P. Schäfers
2012	—	`—`	Hyperelastic image registration: theory, numerical methods, and applications. Lars Ruthotto
2012	J	`jnl`	Motion Correction in Dual Gated Cardiac PET Using Mass-Preserving Image Registration. IEEE Trans. Medical Imaging Fabian Gigengack, Lars Ruthotto, Martin Burger, Carsten H. Wolters, Xiaoyi Jiang, Klaus P. Schäfers
2012	—	`conf`	Registration of Dynamic Contrast Enhanced MRI with Local Rigidity Constraint. WBIR Lars Ruthotto, Erlend Hodneland, Jan Modersitzki
2010	B	`conf`	A variational approach for the correction of field-inhomogeneities in EPI sequences. Image Processing Janine Olesch, Lars Ruthotto, Harald Kugel, Stefan Skare, Bernd Fischer, Carsten H. Wolters