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
Omri AzencotSenior Lecturer (Assistant Professor), BGUVerified email at cs.bgu.ac.il
Alejandro QueirugaGoogleVerified email at google.com
Liam HodgkinsonUniversity of MelbourneVerified email at unimelb.edu.au
Zhewei YaoSnowflakeVerified email at snowflake.com
Soon Hoe LimNordita, KTH Royal Institute of Technology & Stockholm UniversityVerified email at kth.se
Krithika ManoharUniversity of WashingtonVerified email at uw.edu
Miles E. LopesUC DavisVerified email at ucdavis.edu
Dane TaylorSchool of Computing, Math/Stat, EECS, University of WyomingVerified email at uwyo.edu
Winnie XuContextual AI, Stanford UniversityVerified email at cs.toronto.edu
Michael MuehlebachMax Planck Institute for Intelligent SystemsVerified email at tuebingen.mpg.de
Aleksandr AravkinUniversity of WashingtonVerified email at uw.edu
James W DEMMELProfessor of EECS and Mathematics, UC BerkeleyVerified email at berkeley.edu
Jack DongarraUniversity of Tennessee; Oak Ridge National Laboratory; University of ManchesterVerified email at icl.utk.edu
Michał DerezińskiAssistant Professor at University of MichiganVerified email at umich.edu
Aditi KrishnapriyanAssistant Professor, UC 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
Inderjit S. DhillonDistinguished Scientist at Google & Professor of Computer Science at UT Austin, Ex-VP at AmazonVerified email at cs.utexas.edu

N. Benjamin Erichson

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Verified email at pitt.edu - Homepage

Linear Algebra Deep Learning Dynamical Systems


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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	240*	2020
Randomized matrix decompositions using R NB Erichson, S Voronin, SL Brunton, JN Kutz Journal of Statistical Software 89 (1), 1--48, 2019	172	2019
Physics-informed autoencoders for Lyapunov-stable fluid flow prediction NB Erichson, M Muehlebach, MW Mahoney arXiv preprint arXiv:1905.10866, 2019	165	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	158	2020
Randomized dynamic mode decomposition NB Erichson, L Mathelin, JN Kutz, SL Brunton SIAM Journal on Applied Dynamical Systems 18 (4), 1867-1891, 2019	149	2019
Forecasting sequential data using consistent koopman autoencoders O Azencot, NB Erichson, V Lin, M Mahoney International Conference on Machine Learning, 475-485, 2020	140	2020
Compressed dynamic mode decomposition for background modeling NB Erichson, SL Brunton, JN Kutz Journal of Real-Time Image Processing 16, 1479-1492, 2019	125	2019
Lipschitz recurrent neural networks NB Erichson, O Azencot, A Queiruga, L Hodgkinson, MW Mahoney 9th International Conference on Learning Representations (ICLR), 2021	111	2021
Randomized low-rank dynamic mode decomposition for motion detection NB Erichson, C Donovan Computer Vision and Image Understanding 146, 40-50, 2016	88	2016
Adversarially-Trained Deep Nets Transfer Better: Illustration on Image Classification F Utrera, E Kravitz, NB Erichson, R Khanna, MW Mahoney 9th International Conference on Learning Representations (ICLR), 2021	85	2021
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	71	2015
Randomized nonnegative matrix factorization NB Erichson, A Mendible, S Wihlborn, JN Kutz Pattern Recognition Letters 104, 1-7, 2018	67	2018
Randomized CP tensor decomposition NB Erichson, K Manohar, SL Brunton, JN Kutz Machine Learning: Science and Technology 1 (2), 025012, 2020	61	2020
Noisy recurrent neural networks SH Lim, NB Erichson, L Hodgkinson, MW Mahoney Advances in Neural Information Processing Systems 34, 2021	49	2021
Continuous-in-depth neural networks AF Queiruga, NB Erichson, D Taylor, MW Mahoney arXiv preprint arXiv:2008.02389, 2020	48	2020
Long expressive memory for sequence modeling TK Rusch, S Mishra, NB Erichson, MW Mahoney 10th International Conference on Learning Representations (ICLR), 2022	42	2022
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	37	2017
Compressed dynamic mode decomposition for background modeling NB Erichson, SL Brunton, JN Kutz Journal of Real-Time Image Processing 16, 1479-1492, 2019	34*	2019
Randomized numerical linear algebra: A perspective on the field with an eye to software R Murray, J Demmel, MW Mahoney, NB Erichson, M Melnichenko, ... arXiv preprint arXiv:2302.11474, 2023	33	2023
Noisy feature mixup SH Lim, NB Erichson, F Utrera, W Xu, MW Mahoney 10th International Conference on Learning Representations (ICLR), 2022	33	2022

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