N. Benjamin Erichson

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Michael MahoneyProfessor of Statistics, UC BerkeleyVerified email at stat.berkeley.edu
Steven L. BruntonProfessor, University of WashingtonVerified email at uw.edu
J. Nathan KutzProfessor of Applied Mathematics & Electrical and Computer EngineeringVerified email at uw.edu
Alejandro QueirugaGoogleVerified email at google.com
Liam HodgkinsonUniversity of MelbourneVerified email at unimelb.edu.au
Zhewei YaoMicrosoftVerified email at microsoft.com
Omri AzencotSenior Lecturer, BGUVerified email at cs.bgu.ac.il
Krithika ManoharAssistant Professor, University of WashingtonVerified email at uw.edu
Soon Hoe LimNordita Assistant Professor, KTH Royal Institute of Technology and Stockholm UniversityVerified email at su.se
Dane TaylorDepartment of Mathematics, University at Buffalo, SUNYVerified email at buffalo.edu
Miles E. LopesUC DavisVerified email at ucdavis.edu
Aleksandr AravkinUniversity of WashingtonVerified email at uw.edu
Vanessa LinUndergraduate Researcher at University of California, BerkeleyVerified email at berkeley.edu
Rajiv KhannaAssistant Prof, PurdueCSVerified email at purdue.edu
Siddhartha MishraProfessor of Applied Mathematics, ETH Zurich, SwitzerlandVerified email at sam.math.ethz.ch
Winnie XuUniversity of TorontoVerified email at cs.toronto.edu
T. Konstantin RuschETH Zurich, UC BerkeleyVerified email at ethz.ch
Kunihiko TairaUniversity of California, Los AngelesVerified email at seas.ucla.edu
Aditi KrishnapriyanUC BerkeleyVerified email at stanford.edu
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyVerified email at cs.berkeley.edu

N. Benjamin Erichson

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Verified email at pitt.edu - Homepage

Linear Algebra Deep Learning Dynamical Systems


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Randomized matrix decompositions using R NB Erichson, S Voronin, SL Brunton, JN Kutz Journal of Statistical Software 89 (1), 1--48, 2019	140	2019
Compressed dynamic mode decomposition for background modeling NB Erichson, SL Brunton, JN Kutz Journal of Real-Time Image Processing 16, 1479-1492, 2019	120*	2019
Shallow neural networks for fluid flow reconstruction with limited sensors NB Erichson, L Mathelin, Z Yao, SL Brunton, MW Mahoney, JN Kutz Proceedings of the Royal Society A 476 (2238), 20200097, 2020	114*	2020
Physics-informed autoencoders for Lyapunov-stable fluid flow prediction NB Erichson, M Muehlebach, MW Mahoney arXiv preprint arXiv:1905.10866, 2019	114	2019
Randomized dynamic mode decomposition NB Erichson, L Mathelin, JN Kutz, SL Brunton SIAM Journal on Applied Dynamical Systems 18 (4), 1867-1891, 2019	112	2019
Sparse principal component analysis via variable projection NB Erichson, P Zheng, K Manohar, SL Brunton, JN Kutz, AY Aravkin SIAM Journal on Applied Mathematics 80 (2), 977-1002, 2020	105	2020
Randomized low-rank dynamic mode decomposition for motion detection NB Erichson, C Donovan Computer Vision and Image Understanding 146, 40-50, 2016	77	2016
Forecasting sequential data using consistent koopman autoencoders O Azencot, NB Erichson, V Lin, M Mahoney International Conference on Machine Learning, 475-485, 2020	65	2020
Multi-resolution dynamic mode decomposition for foreground/background separation and object tracking JN Kutz, X Fu, SL Brunton, NB Erichson 2015 IEEE International Conference on Computer Vision Workshop (ICCVW), 921-929, 2015	59	2015
Lipschitz recurrent neural networks NB Erichson, O Azencot, A Queiruga, L Hodgkinson, MW Mahoney International Conference on Learning Representations, 2021	55	2021
Adversarially-Trained Deep Nets Transfer Better: Illustration on Image Classification F Utrera, E Kravitz, NB Erichson, R Khanna, MW Mahoney International Conference on Learning Representations, 2021	54	2021
Randomized nonnegative matrix factorization NB Erichson, A Mendible, S Wihlborn, JN Kutz Pattern Recognition Letters 104, 1-7, 2018	54	2018
Randomized CP tensor decomposition NB Erichson, K Manohar, SL Brunton, JN Kutz Machine Learning: Science and Technology 1 (2), 025012, 2020	47	2020
Compressed Singular Value Decomposition for Image and Video Processing N Benjamin Erichson, SL Brunton, J Nathan Kutz Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017	28	2017
Continuous-in-depth neural networks AF Queiruga, NB Erichson, D Taylor, MW Mahoney arXiv preprint arXiv:2008.02389, 2020	27	2020
scikit-cuda 0.5. 3: a Python interface to GPU-powered libraries LE Givon, T Unterthiner, NB Erichson, DW Chiang, E Larson, L Pfister, ... http://dx.doi.org/10.5281/zenodo.3229433 30, v1, 2019	27*	2019
Noisy recurrent neural networks SH Lim, NB Erichson, L Hodgkinson, MW Mahoney Advances in Neural Information Processing Systems 34, 2021	20	2021
Retinamatch: Efficient template matching of retina images for teleophthalmology C Gong, NB Erichson, JP Kelly, L Trutoiu, BT Schowengerdt, SL Brunton, ... IEEE transactions on medical imaging 38 (8), 1993-2004, 2019	17	2019
Noise-response analysis of deep neural networks quantifies robustness and fingerprints structural malware NB Erichson, D Taylor, Q Wu, MW Mahoney Proceedings of the 2021 SIAM International Conference on Data Mining (SDM …, 2021	15*	2021
Jumprelu: A retrofit defense strategy for adversarial attacks NB Erichson, Z Yao, MW Mahoney arXiv preprint arXiv:1904.03750, 2019	12	2019

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