Joshua L. Proctor
Joshua L. Proctor
Principal Scientist and Research Manager, Institute for Disease Modeling, Affiliate Assistant
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
11402016
Dynamic mode decomposition: data-driven modeling of complex systems
JN Kutz, SL Brunton, BW Brunton, JL Proctor
Society for Industrial and Applied Mathematics, 2016
5352016
Data-driven discovery of partial differential equations
SH Rudy, SL Brunton, JL Proctor, JN Kutz
Science Advances 3 (4), e1602614, 2017
4902017
Dynamic Mode Decomposition with control
JL Proctor, SL Brunton, JN Kutz
SIAM Journal on Applied Dynamical Systems 15 (1), 142–161, 2016
3672016
Dynamic mode decomposition with control
JL Proctor, SL Brunton, JN Kutz
SIAM Journal on Applied Dynamical Systems 15 (1), 142-161, 2016
3672016
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
2172016
Chaos as an intermittently forced linear system
SL Brunton, BW Brunton, JL Proctor, E Kaiser, JN Kutz
Nature communications 8 (1), 1-9, 2017
1962017
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
1642016
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
1372015
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
1212017
Discovering dynamic patterns from infectious disease data using dynamic mode decomposition
JL Proctor, PA Eckhoff
International health 7 (2), 139-145, 2015
1142015
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
1052018
COMPRESSED SENSING AND DYNAMIC MODE DECOMPOSITION.
SL Brunton, JL Proctor, JH Tu, JN Kutz
Journal of computational dynamics 2 (2), 2015
902015
Passive mode-locking by use of waveguide arrays
JL Proctor, JN Kutz
Optics letters 30 (15), 2013-2015, 2005
832005
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
712005
Sparse identification of nonlinear dynamics with control (SINDYc)
SL Brunton, JL Proctor, JN Kutz
IFAC-PapersOnLine 49 (18), 710-715, 2016
622016
Neuromechanical models for insect locomotion: Stability, maneuverability, and proprioceptive feedback
R Kukillaya, JL Proctor, P Holmes
Chaos 19 (2), 2009
612009
Reflexes and preflexes: On the role of sensory feedback on rhythmic patterns in legged locomotion
JL Proctor, P Holmes
Biological Cybernetics 102 (6), 513-531, 2010
562010
Exploiting sparsity and equation-free architectures in complex systems
JL Proctor, SL Brunton, BW Brunton, JN Kutz
The European Physical Journal Special Topics 223 (13), 2665-2684, 2014
462014
Compressive sampling and dynamic mode decomposition
SL Brunton, JL Proctor, JN Kutz
arXiv preprint arXiv:1312.5186, 2013
432013
Il sistema al momento non può eseguire l'operazione. Riprova più tardi.
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