
Publications
A Unified Framework for Sparse Relaxed Regularized Regression: SR3 | P. Zheng, T. Askham, S. L. Brunton, J. N. Kutz, and A. Y. Aravkin IEEE Access, 7(1):1404--1423, 2019 | |
Deep learning for universal linear embeddings of nonlinear dynamics | B. Lusch, J. N. Kutz, S. L. Brunton Nature Communications, 9(1):4950, 2018 | |
Sparse identification of nonlinear dynamics for model predictive control in the low-data limit | E. Kaiser, J. N. Kutz, and S. L. Brunton Proceedings of the Royal Society A, 474(2219), 2018 | |
Neural-inspired sensors enable sparse, efficient classification of spatiotemporal data | T. Mohren, T. L. Daniel, S. L. Brunton, and B. W. Brunton Proceedings of the National Academy of Sciences, 115(42):10564–10569, 2018 | |
Predicting shim gaps in aircraft assembly with machine learning and sparse sensing | K. Manohar, T. Hogan, J. Buttrick, A. G. Banerjee, J. N. Kutz, and S. L. Brunton Journal of Manufacturing Systems, 48(C):87-95, 2018 | |
Data-Driven Sparse Sensor Placement for Reconstruction: Demonstrating the Benefits of Exploiting Known Patterns | K. Manohar, B. W. Brunton, J. N. Kutz, and , S. L. Brunton IEEE Control Systems Magazine, 38(3):63-86, 2018 | |
Sparse reduced-order modeling: Sensor-based dynamics to full-state estimation | J. C. Loiseau, B. R. Noack, and S. L. Brunton Journal of Fluid Mechanics, 844:459–490, 2018 | |
Constrained sparse Galerkin regression | J. C. Loiseau and S. L. Brunton Journal of Fluid Mechanics, 838:42–67, 2018 | |
Modal Analysis of Fluid Flows: An Overview | K. Taira, S. L. Brunton, S. T. M. Dawson, C. W. Rowley, T. Colonius, B. J. McKeon, O. Schmidt, S. Gordeyev, V. Theofilis, and L. S. Ukeiley AIAA Journal, 55(12):4013–4041, 2017 | |
Intracycle angular velocity control of cross-flow turbines | B. Strom, S. L. Brunton, and B. Polagye Nature Energy, 2(17103):1–9, 2017 | |
Chaos as an intermittently forced linear system | S. L. Brunton, B. W. Brunton, J. L. Proctor, E. Kaiser, and J. N. Kutz Nature Communications, 8(19):1–9, 2017 | |
Data-driven discovery of partial differential equations | S. H. Rudy, S. L. Brunton, J. L. Proctor, and J. N. Kutz Science Advances, 3:e1602614, 2017 |