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Joshua L. Proctor
Joshua L. Proctor
Principal Research Scientist, Bill and Melinda Gates Foundation
Email verificata su idmod.org
Titolo
Citata da
Citata da
Anno
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
37182016
Dynamic mode decomposition: data-driven modeling of complex systems
JN Kutz, SL Brunton, BW Brunton, JL Proctor
Society for Industrial and Applied Mathematics, 2016
15852016
Data-driven discovery of partial differential equations
SH Rudy, SL Brunton, JL Proctor, JN Kutz
Science advances 3 (4), e1602614, 2017
13642017
Dynamic Mode Decomposition with control
JL Proctor, SL Brunton, JN Kutz
SIAM Journal on Applied Dynamical Systems 15 (1), 142–161, 2016
9532016
Dynamic mode decomposition with control
JL Proctor, SL Brunton, JN Kutz
SIAM Journal on Applied Dynamical Systems 15 (1), 142-161, 2016
9532016
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
5412016
Chaos as an intermittently forced linear system
SL Brunton, BW Brunton, JL Proctor, E Kaiser, JN Kutz
Nature communications 8 (1), 19, 2017
5272017
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
3882016
Generalizing Koopman theory to allow for inputs and control
JL Proctor, SL Brunton, JN Kutz
SIAM Journal on Applied Dynamical Systems 17 (1), 909-930, 2018
3342018
Sparse identification of nonlinear dynamics with control (SINDYc)
SL Brunton, JL Proctor, JN Kutz
IFAC-PapersOnLine 49 (18), 710-715, 2016
2892016
Model selection for dynamical systems via sparse regression and information criteria
NM Mangan, JN Kutz, SL Brunton, JL Proctor
Proceedings of the Royal Society A: Mathematical, Physical and Engineering …, 2017
2772017
Discovering dynamic patterns from infectious disease data using dynamic mode decomposition
JL Proctor, PA Eckhoff
International health 7 (2), 139-145, 2015
2232015
Modeling malaria genomics reveals transmission decline and rebound in Senegal
RF Daniels, SF Schaffner, EA Wenger, JL Proctor, HH Chang, W Wong, ...
Proceedings of the National Academy of Sciences 112 (22), 7067-7072, 2015
1862015
Compressed sensing and dynamic mode decomposition
SL Brunton, JL Proctor, JH Tu, JN Kutz
Journal of computational dynamics 2 (2), 165-191, 2016
1582016
Model selection for hybrid dynamical systems via sparse regression
NM Mangan, T Askham, SL Brunton, JN Kutz, JL Proctor
Proceedings of the Royal Society A 475 (2223), 20180534, 2019
1022019
Passive mode-locking by use of waveguide arrays
JL Proctor, JN Kutz
Optics letters 30 (15), 2013-2015, 2005
942005
Dynamic mode decomposition for compressive system identification
Z Bai, E Kaiser, JL Proctor, JN Kutz, SL Brunton
AIAA Journal 58 (2), 561-574, 2020
902020
Sparse sensor placement optimization for classification
BW Brunton, SL Brunton, JL Proctor, JN Kutz
SIAM Journal on Applied Mathematics 76 (5), 2099-2122, 2016
882016
Applied Koopman theory for partial differential equations and data-driven modeling of spatio-temporal systems
J Nathan Kutz, JL Proctor, SL Brunton
Complexity 2018, 1-16, 2018
842018
Nonlinear mode-coupling for passive mode-locking: application of waveguide arrays, dual-core fibers, and/or fiber arrays
J Proctor, JN Kutz
Optics express 13 (22), 8933-8950, 2005
802005
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