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Steven L. Brunton
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Discovering governing equations from data by sparse identification of nonlinear dynamical systems
SL Brunton, JL Proctor, JN Kutz
Proceedings of the national academy of sciences 113 (15), 3932-3937, 2016
39862016
Data-driven science and engineering: Machine learning, dynamical systems, and control
SL Brunton, JN Kutz
Cambridge University Press, 2022
24292022
Machine learning for fluid mechanics
SL Brunton, BR Noack, P Koumoutsakos
Annual review of fluid mechanics 52, 477-508, 2020
22462020
On dynamic mode decomposition: Theory and applications
JH Tu, CW Rowley, DM Luchtenburg, SL Brunton, JN Kutz
Journal of Computational Dynamics 1 (2), 391-421, 2014
20522014
Dynamic mode decomposition: data-driven modeling of complex systems
JN Kutz, SL Brunton, BW Brunton, JL Proctor
Society for Industrial and Applied Mathematics, 2016
16612016
Modal analysis of fluid flows: An overview
K Taira, SL Brunton, STM Dawson, CW Rowley, T Colonius, BJ McKeon, ...
Aiaa Journal 55 (12), 4013-4041, 2017
15902017
Data-driven discovery of partial differential equations
SH Rudy, SL Brunton, JL Proctor, JN Kutz
Science advances 3 (4), e1602614, 2017
14452017
Deep learning for universal linear embeddings of nonlinear dynamics
B Lusch, JN Kutz, SL Brunton
Nature communications 9 (1), 4950, 2018
12082018
Dynamic mode decomposition with control
JL Proctor, SL Brunton, JN Kutz
SIAM Journal on Applied Dynamical Systems 15 (1), 142-161, 2016
10122016
Data-driven discovery of coordinates and governing equations
K Champion, B Lusch, JN Kutz, SL Brunton
Proceedings of the National Academy of Sciences 116 (45), 22445-22451, 2019
7612019
Closed-loop turbulence control: Progress and challenges
SL Brunton, BR Noack
Applied Mechanics Reviews 67 (5), 050801, 2015
5992015
Sparse identification of nonlinear dynamics for model predictive control in the low-data limit
E Kaiser, JN Kutz, SL Brunton
Proceedings of the Royal Society A 474 (2219), 20180335, 2018
5852018
Koopman invariant subspaces and finite linear representations of nonlinear dynamical systems for control
SL Brunton, BW Brunton, JL Proctor, JN Kutz
PloS one 11 (2), e0150171, 2016
5632016
Chaos as an intermittently forced linear system
SL Brunton, BW Brunton, JL Proctor, E Kaiser, JN Kutz
Nature Communications 8 (19), 1--9, 2017
5482017
Modal analysis of fluid flows: Applications and outlook
K Taira, MS Hemati, SL Brunton, Y Sun, K Duraisamy, S Bagheri, ...
AIAA journal 58 (3), 998-1022, 2020
4772020
Maximum power point tracking for photovoltaic optimization using ripple-based extremum seeking control
SL Brunton, CW Rowley, SR Kulkarni, C Clarkson
Power Electronics, IEEE Transactions on 25 (10), 2531-2540, 2010
4392010
Inferring biological networks by sparse identification of nonlinear dynamics
NM Mangan, SL Brunton, JL Proctor, JN Kutz
IEEE Transactions on Molecular, Biological and Multi-Scale Communications 2 …, 2016
4112016
Multiresolution dynamic mode decomposition
JN Kutz, X Fu, SL Brunton
SIAM Journal on Applied Dynamical Systems 15 (2), 713-735, 2016
4102016
Data-driven sparse sensor placement for reconstruction: Demonstrating the benefits of exploiting known patterns
K Manohar, BW Brunton, JN Kutz, SL Brunton
IEEE Control Systems Magazine 38 (3), 63-86, 2018
3952018
Machine learning control-taming nonlinear dynamics and turbulence
T Duriez, SL Brunton, BR Noack
Springer International Publishing, 2017
3942017
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