Model selection for dynamical systems via sparse regression and information criteria
Proceedings of the Royal Society A: Mathematical …, 2017 - royalsocietypublishing.org
We develop an algorithm for model selection which allows for the consideration of a
combinatorially large number of candidate models governing a dynamical system. The …
combinatorially large number of candidate models governing a dynamical system. The …
Model selection for dynamical systems via sparse regression and information criteria
NM Mangan, JN Kutz, SL Brunton… - Proceedings of the …, 2017 - scholars.northwestern.edu
We develop an algorithm for model selection which allows for the consideration of a
combinatorially large number of candidate models governing a dynamical system. The …
combinatorially large number of candidate models governing a dynamical system. The …
[PDF][PDF] Model selection for dynamical systems via sparse regression and information criteria
NM Mangan, JN Kutz, SL Brunton… - arXiv preprint arXiv …, 2017 - researchgate.net
We develop an algorithm for model selection which allows for the consideration of a
combinatorially large number of candidate models governing a dynamical system. The …
combinatorially large number of candidate models governing a dynamical system. The …
[HTML][HTML] Model selection for dynamical systems via sparse regression and information criteria
NM Mangan, JN Kutz, SL Brunton… - Proceedings …, 2017 - ncbi.nlm.nih.gov
We develop an algorithm for model selection which allows for the consideration of a
combinatorially large number of candidate models governing a dynamical system. The …
combinatorially large number of candidate models governing a dynamical system. The …
Model selection for dynamical systems via sparse regression and information criteria
NM Mangan, JN Kutz, SL Brunton… - Proceedings of the …, 2017 - ui.adsabs.harvard.edu
We develop an algorithm for model selection which allows for the consideration of a
combinatorially large number of candidate models governing a dynamical system. The …
combinatorially large number of candidate models governing a dynamical system. The …
Model selection for dynamical systems via sparse regression and information criteria
NM Mangan, JN Kutz, SL Brunton… - arXiv preprint arXiv …, 2017 - arxiv.org
We develop an algorithm for model selection which allows for the consideration of a
combinatorially large number of candidate models governing a dynamical system. The …
combinatorially large number of candidate models governing a dynamical system. The …
Model selection for dynamical systems via sparse regression and information criteria
NM Mangan, JN Kutz, SL Brunton… - Proc. Roy. Soc. Lond …, 2017 - inspirehep.net
We develop an algorithm for model selection which allows for the consideration of a
combinatorially large number of candidate models governing a dynamical system. The …
combinatorially large number of candidate models governing a dynamical system. The …
Model selection for dynamical systems via sparse regression and information criteria
NM Mangan, JN Kutz, SL Brunton… - Proceedings …, 2017 - pubmed.ncbi.nlm.nih.gov
We develop an algorithm for model selection which allows for the consideration of a
combinatorially large number of candidate models governing a dynamical system. The …
combinatorially large number of candidate models governing a dynamical system. The …
Model selection for dynamical systems via sparse regression and information criteria.
NM Mangan, JN Kutz, SL Brunton… - Proceedings …, 2017 - europepmc.org
We develop an algorithm for model selection which allows for the consideration of a
combinatorially large number of candidate models governing a dynamical system. The …
combinatorially large number of candidate models governing a dynamical system. The …