Publications

Dimensionally consistent learning with Buckingham Pi	Bakarji, J., Callaham, J., Brunton, S.L. et al. Dimensionally consistent learning with Buckingham Pi. Nat Comput Sci 2, 834–844 (2022).
A concise guide to modelling the physics of embodied intelligence in soft robotics	Mengaldo, G., Renda, F., Brunton, S.L. et al. A concise guide to modelling the physics of embodied intelligence in soft robotics. Nat Rev Phys 4, 595–610 (2022).
Enhancing computational fluid dynamics with machine learning	Vinuesa, R., Brunton, S.L. Enhancing computational fluid dynamics with machine learning. Nat Comput Sci 2, 358–366 (2022).
An empirical mean-field model of symmetry-breaking in a turbulent wake	Callaham JL, Rigas G, Loiseau JC, Brunton SL. An empirical mean-field model of symmetry-breaking in a turbulent wake. Sci Adv. 2022 May 13;8(19):eabm4786. doi: 10.1126/sciadv.abm4786. Epub 2022 May 11. PMID: 35544559; PMCID: PMC9094670.
Ensemble-SINDy: Robust sparse model discovery in the low-data, high-noise limit, with active learning and control	Fasel U, Kutz JN, Brunton BW, Brunton SL. 2022 Ensemble-SINDy: Robust sparse model discovery in the low-data, high-noise limit, with active learning and control.Proc. R. Soc. A 478: 20210904.
Modern Koopman Theory for Dynamical Systems	Brunton, Steven & Budišić, Marko & Kaiser, Eurika & Kutz, J.. (2021). Modern Koopman Theory for Dynamical Systems.
Kernel learning for robust dynamic mode decomposition: linear and nonlinear disambiguation optimization	Baddoo PJ, Herrmann B, McKeon BJ, Brunton SL. 2022 Kernel learning for robust dynamic mode decomposition: linear and nonlinear disambiguation optimization.Proc. R. Soc. A 478: 20210830.
Optimal Sensor and Actuator Selection Using Balanced Model Reduction	K. Manohar, J. N. Kutz and S. L. Brunton, "Optimal Sensor and Actuator Selection Using Balanced Model Reduction," in IEEE Transactions on Automatic Control, vol. 67, no. 4, pp. 2108-2115, April 2022, doi: 10.1109/TAC.2021.3082502.
On the role of nonlinear correlations in reduced-order modelling	Jared L. Callaham, Steven L. Brunton, Jean-Christophe Loiseau. On the role of nonlinear correlations in reduced-order modelling. Journal of Fluid Mechanics, 2022, 938, pp.A1. ff10.1017/jfm.2021.994ff. ffhal-03909105f
PySINDy: A comprehensive Python package for robust sparse system identification	Alan A. Kaptanoglu, Brian M. de Silva, Urban Fasel, Kadierdan Kaheman, Andy J. Goldschmidt, Jared Callaham, Charles B. Delahunt, Zachary G. Nicolaou, Kathleen Champion, Jean-Christophe Loiseau, J. Nathan Kutz, Steven L. Brunton PySINDy: A comprehensive Python package for robust sparse system identification. Journal of Open Source Software, 7(69), 3994,
Applying machine learning to study fluid mechanics	Brunton, S.L. Applying machine learning to study fluid mechanics. Acta Mech. Sin. 37, 1718–1726 (2021).
Promoting global stability in data-driven models of quadratic nonlinear dynamics	A. A. Kaptanoglu, J. L. Callaham, C. J. Hansen, A. Aravkin, and S. L. Brunton Promoting global stability in data-driven models of quadratic nonlinear dynamics. Physical Review Fluids, 6:094401, 2021. (Editors’ Suggestion)