Seuraa
Brian R Hunt
Brian R Hunt
Vahvistettu sähköpostiosoite verkkotunnuksessa umd.edu
Nimike
Viittaukset
Viittaukset
Vuosi
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
18322007
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
10512004
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
10352018
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
586*1992
A guide to MATLAB: for beginners and experienced users
BR Hunt, RL Lipsman, J Rosenberg
Cambridge Univ Pr, 2006
528*2006
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
5212017
Long time evolution of phase oscillator systems
E Ott, TM Antonsen
Chaos: An interdisciplinary journal of nonlinear science 19 (2), 2009
4972009
Reducing storage requirements for biological sequence comparison
M Roberts, W Hayes, BR Hunt, SM Mount, JA Yorke
Bioinformatics 20 (18), 3363-3369, 2004
4222004
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
353*2005
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
3482020
Onset of synchronization in large networks of coupled oscillators
JG Restrepo, E Ott, BR Hunt
Physical Review E 71 (3), 036151, 2005
3402005
Attractor reconstruction by machine learning
Z Lu, BR Hunt, E Ott
Chaos: An Interdisciplinary Journal of Nonlinear Science 28 (6), 2018
3102018
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
3032004
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
2892017
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
2822018
Characterizing the dynamical importance of network nodes and links
JG Restrepo, E Ott, BR Hunt
Physical review letters 97 (9), 94102, 2006
2782006
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
2772011
Differentiable generalized synchronization of chaos
BR Hunt, E Ott, JA Yorke
Physical Review E 55 (4), 4029, 1997
2541997
Local low dimensionality of atmospheric dynamics
DJ Patil, BR Hunt, E Kalnay, JA Yorke, E Ott
Physical Review Letters 86 (26), 5878, 2001
2432001
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
2382008
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Artikkelit 1–20