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 | 232* | 2020 |
Randomized matrix decompositions using R NB Erichson, S Voronin, SL Brunton, JN Kutz Journal of Statistical Software 89 (1), 1--48, 2019 | 170 | 2019 |
Physics-informed autoencoders for Lyapunov-stable fluid flow prediction NB Erichson, M Muehlebach, MW Mahoney arXiv preprint arXiv:1905.10866, 2019 | 164 | 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 | 155 | 2020 |
Randomized dynamic mode decomposition NB Erichson, L Mathelin, JN Kutz, SL Brunton SIAM Journal on Applied Dynamical Systems 18 (4), 1867-1891, 2019 | 147 | 2019 |
Forecasting sequential data using consistent koopman autoencoders O Azencot, NB Erichson, V Lin, M Mahoney International Conference on Machine Learning, 475-485, 2020 | 136 | 2020 |
Compressed dynamic mode decomposition for background modeling NB Erichson, SL Brunton, JN Kutz Journal of Real-Time Image Processing 16, 1479-1492, 2019 | 123 | 2019 |
Lipschitz recurrent neural networks NB Erichson, O Azencot, A Queiruga, L Hodgkinson, MW Mahoney 9th International Conference on Learning Representations (ICLR), 2021 | 106 | 2021 |
Randomized low-rank dynamic mode decomposition for motion detection NB Erichson, C Donovan Computer Vision and Image Understanding 146, 40-50, 2016 | 87 | 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 | 69 | 2015 |
Randomized nonnegative matrix factorization NB Erichson, A Mendible, S Wihlborn, JN Kutz Pattern Recognition Letters 104, 1-7, 2018 | 66 | 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 | 40 | 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 |
Noisy feature mixup SH Lim, NB Erichson, F Utrera, W Xu, MW Mahoney 10th International Conference on Learning Representations (ICLR), 2022 | 33 | 2022 |
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 | 30 | 2023 |