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SINDy is a method for learning system of differential equations from data by solving a sparse linear regression optimization problem [Brunton et al., 2016].
Deterministic nonperiodic flow
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SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python
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Relation between observability and differential embeddings for nonlinear dynamics
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Piecewise affine models of chaotic attractors: The rossler and lorenz systems
G. Amaral, C. Letellier, and L. Aguirre · 2006
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Pathwise coordinate optimization
J. Friedman, T. Hastie, H. Höfling, and R. Tibshirani · 2007
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Scikit-learn: Machine learning in Python
F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg, J. Vanderplas, A. Passos, D. Cournapeau, M. Brucher, M. Perrot, and E. Duchesnay · 2011
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Polynomial search and global modeling: Two algorithms for modeling chaos
S. Mangiarotti, R. Coudret, L. Drapeau, and L. Jarlan · 2012
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Statistical learning with sparsity: the lasso and generalizations
T. Hastie, R. Tibshirani, and M. Wainwright · 2015
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Discovering governing equations from data by sparse identification of nonlinear dynamical systems
Data-driven discovery of partial differential equations
S. H. Rudy, S. L. Brunton, J. L. Proctor, and J. N. Kutz · 2017
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Chaotic behaviour of the rossler model and its analysis by using bifurcations of limit cycles and chaotic attractors
K. M. Ibrahim, R. K. Jamal, and F. H. Ali · 2018
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Sparse identification of nonlinear dynamics for rapid model recovery
M. Quade, M. Abel, J. Nathan Kutz, and S. L. Brunton · 2018
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sktime: A Unified Interface for Machine Learning with Time Series
M. Löning, A. Bagnall, S. Ganesh, V. Kazakov, J. Lines, and F. J. Király · 2019
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GPoM:Generalized Polynomial Modelling , 2020
S. Mangiarotti, M. Huc, F. L. Jean, M. Chassan, L. Drapeau, I. de Recherche pour le Développement, and C. N. de la Recherche Scientifique and · 2020
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R: A Language and Environment for Statistical Computing
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S. L. Brunton, J. L. Proctor, and J. N. Kutz · 2016
Cited alongside, same era.
Automated reverse engineering of nonlinear dynamical systems
J. Bongard and H. Lipson
Cited in the paper.
Automated reverse engineering of nonlinear dynamical systems
J. Bongard and H. Lipson
Cited in the paper.
R Core Team · 2020
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