Efficient data assimilation for spatiotemporal chaos: a local ensemble transform Kalman filter BR Hunt, EJ Kostelich, I Szunyogh Physica D: Nonlinear Phenomena 230 (1-2), 112-126, 2007 | 1922 | 2007 |
Model-free prediction of large spatiotemporally chaotic systems from data: A reservoir computing approach J Pathak, B Hunt, M Girvan, Z Lu, E Ott Physical review letters 120 (2), 024102, 2018 | 1222 | 2018 |
A local ensemble Kalman filter for atmospheric data assimilation E Ott, BR Hunt, I Szunyogh, AV Zimin, EJ Kostelich, M Corazza, E Kalnay, ... Tellus A 56 (5), 415-428, 2004 | 1076 | 2004 |
Using machine learning to replicate chaotic attractors and calculate Lyapunov exponents from data J Pathak, Z Lu, BR Hunt, M Girvan, E Ott Chaos: An Interdisciplinary Journal of Nonlinear Science 27 (12), 2017 | 630 | 2017 |
Prevalence: a translation-invariant “almost every” on infinite-dimensional spaces BR Hunt, T Sauer, JA Yorke Bulletin of the American mathematical society 27 (2), 217-238, 1992 | 596 | 1992 |
A guide to MATLAB: for beginners and experienced users BR Hunt, RL Lipsman, J Rosenberg Cambridge Univ Pr, 2006 | 550* | 2006 |
Long time evolution of phase oscillator systems E Ott, TM Antonsen Chaos: An interdisciplinary journal of nonlinear science 19 (2), 2009 | 526 | 2009 |
Reducing storage requirements for biological sequence comparison M Roberts, W Hayes, BR Hunt, SM Mount, JA Yorke Bioinformatics 20 (18), 3363-3369, 2004 | 489 | 2004 |
Backpropagation algorithms and reservoir computing in recurrent neural networks for the forecasting of complex spatiotemporal dynamics PR Vlachas, J Pathak, BR Hunt, TP Sapsis, M Girvan, E Ott, ... Neural Networks 126, 191-217, 2020 | 446 | 2020 |
Attractor reconstruction by machine learning Z Lu, BR Hunt, E Ott Chaos: An Interdisciplinary Journal of Nonlinear Science 28 (6), 2018 | 370 | 2018 |
Assessing a local ensemble Kalman filter: perfect model experiments with the National Centers for Environmental Prediction global model I Szunyogh, EJ Kostelich, G Gyarmati, DJ Patil, BR Hunt, E Kalnay, E Ott, ... Tellus A 57 (4), 528-545, 2005 | 355* | 2005 |
Onset of synchronization in large networks of coupled oscillators JG Restrepo, E Ott, BR Hunt Physical Review E 71 (3), 036151, 2005 | 352 | 2005 |
Hybrid forecasting of chaotic processes: Using machine learning in conjunction with a knowledge-based model J Pathak, A Wikner, R Fussell, S Chandra, BR Hunt, M Girvan, E Ott Chaos: An Interdisciplinary Journal of Nonlinear Science 28 (4), 2018 | 345 | 2018 |
Reservoir observers: Model-free inference of unmeasured variables in chaotic systems Z Lu, J Pathak, B Hunt, M Girvan, R Brockett, E Ott Chaos: An Interdisciplinary Journal of Nonlinear Science 27 (4), 2017 | 331 | 2017 |
Four‐dimensional ensemble Kalman filtering BR Hunt, E Kalnay, EJ Kostelich, E Ott, DJ Patil, T Sauer, I Szunyogh, ... Tellus A 56 (4), 273-277, 2004 | 303 | 2004 |
Balance and ensemble Kalman filter localization techniques SJ Greybush, E Kalnay, T Miyoshi, K Ide, BR Hunt Monthly Weather Review 139 (2), 511-522, 2011 | 298 | 2011 |
Characterizing the dynamical importance of network nodes and links JG Restrepo, E Ott, BR Hunt Physical review letters 97 (9), 94102, 2006 | 284 | 2006 |
Differentiable generalized synchronization of chaos BR Hunt, E Ott, JA Yorke Physical Review E 55 (4), 4029, 1997 | 257 | 1997 |
A local ensemble transform Kalman filter data assimilation system for the NCEP global model I Szunyogh, EJ Kostelich, G Gyarmati, E Kalnay, BR Hunt, E Ott, ... Tellus A 60 (1), 113-130, 2008 | 245 | 2008 |
Local low dimensionality of atmospheric dynamics DJ Patil, BR Hunt, E Kalnay, JA Yorke, E Ott Physical Review Letters 86 (26), 5878, 2001 | 244 | 2001 |