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Nature Computational Science|January 4, 2024
Dimensionally consistent learning with Buckingham PiJoseph Bakarji, Jared Callaham, Steven L Brunton, et al.Nature Computational Science|June 28, 2024
Promising directions of machine learning for partial differential equationsSteven L Brunton, J Nathan KutzProceedings. Mathematical, Physical, and Engineering Sciences|November 20, 2020
SINDy-PI: a robust algorithm for parallel implicit sparse identification of nonlinear dynamicsKadierdan Kaheman, J Nathan Kutz, Steven L BruntonPhilosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences|June 20, 2022
Hierarchical deep learning of multiscale differential equation time-steppersYuying Liu, J Nathan Kutz, Steven L BruntonNature Communications|November 25, 2018
Deep learning for universal linear embeddings of nonlinear dynamicsBethany Lusch, J Nathan Kutz, Steven L BruntonOptics Express|April 11, 2014
Classification of birefringence in mode-locked fiber lasers using machine learning and sparse representationXing Fu, Steven L Brunton, J Nathan KutzSensors (Basel, Switzerland)|June 27, 2024
Mobile Sensor Path Planning for Kalman Filter Spatiotemporal EstimationJiazhong Mei, Steven L Brunton, J Nathan KutzPhysical Review. E, Statistical, Nonlinear, and Soft Matter Physics|October 15, 2015
Nonlinear model reduction for dynamical systems using sparse sensor locations from learned librariesSyuzanna Sargsyan, Steven L Brunton, J Nathan KutzProceedings of the National Academy of Sciences of the United States of America|April 2, 2016
Discovering governing equations from data by sparse identification of nonlinear dynamical systemsSteven L Brunton, Joshua L Proctor, J Nathan KutzChaos (Woodbury, N.Y.)|July 2, 2018
Sparse identification of nonlinear dynamics for rapid model recoveryMarkus Quade, Markus Abel, J Nathan Kutz, et al.Pageof 15