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Proceedings. Mathematical, Physical, and Engineering Sciences|April 22, 2022
Ensemble-SINDy: Robust sparse model discovery in the low-data, high-noise limit, with active learning and controlU Fasel, J N Kutz, B W Brunton, et al.Proceedings. Mathematical, Physical, and Engineering Sciences|August 25, 2020
Data-driven nonlinear aeroelastic models of morphing wings for controlN Fonzi, S L Brunton, U FaselProceedings. Mathematical, Physical, and Engineering Sciences|March 7, 2019
Sparse identification of nonlinear dynamics for model predictive control in the low-data limitE Kaiser, J N Kutz, S L BruntonProceedings. Mathematical, Physical, and Engineering Sciences|September 8, 2017
Model selection for dynamical systems via sparse regression and information criteriaN M Mangan, J N Kutz, S L Brunton, et al.Proceedings. Mathematical, Physical, and Engineering Sciences|April 23, 2019
Model selection for hybrid dynamical systems via sparse regressionN M Mangan, T Askham, S L Brunton, et al.Journal of Neural Engineering|February 28, 2020
Signal recovery from stimulation artifacts in intracranial recordings with dictionary learningD J Caldwell, J A Cronin, R P N Rao, et al.Optics Letters|October 31, 2009
Enhanced power transfer and mode coupling in spun twin-core optical fibersJ N Kutz, D J MurakiOptics Letters|December 19, 2007
Noise-induced amplitude and chirp jitter in dispersion-managed soliton communicationsJ N Kutz, P K WaiOptics Letters|December 20, 2007
Dispersion-managed breathers with average normal dispersionJ N Kutz, S G EvangelidesPageof 3