Steven L. Brunton

172 papers A* 1C 2Misc 1Journal 156Unranked 11

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Explainable AI: Learning from the Learners. CoRR Ricardo Vinuesa, Steven L. Brunton, Gianmarco Mengaldo
2026	J	`jnl`	OpenReservoirComputing: GPU-Accelerated Reservoir Computing in JAX. CoRR Jan P. Williams, Dima Tretiak, Steven L. Brunton, J. Nathan Kutz, Krithika Manohar
2026	J	`jnl`	PySensors 2.0: A Python Package for Sparse Sensor Placement. J. Open Source Softw. Niharika Karnik, Yash Bhangale, Mohammad G. Abdo, Andrei A. Klishin, Joshua J. Cogliati, Bingni W. Brunton, J. Nathan Kutz, Steven L. Brunton, Krithika Manohar
2026	J	`jnl`	SINDy-KANs: Sparse identification of non-linear dynamics through Kolmogorov-Arnold networks. CoRR Amanda A. Howard, Nicholas Zolman, Bruno Jacob, Steven L. Brunton, Panos Stinis
2026	J	`jnl`	Trustworthy Koopman Operator Learning: Invariance Diagnostics and Error Bounds. CoRR Gustav Conradie, Nicolas Boullé, Jean-Christophe Loiseau, Steven L. Brunton, Matthew J. Colbrook
2026	J	`jnl`	VENI, VINDy, VICI: A generative reduced-order modeling framework with uncertainty quantification. Neural Networks Paolo Conti, Jonas Kneifl, Andrea Manzoni, Attilio Frangi, Jörg Fehr, Steven L. Brunton, J. Nathan Kutz
2025	J	`jnl`	A Unified Framework to Enforce, Discover, and Promote Symmetry in Machine Learning. J. Mach. Learn. Res. Samuel E. Otto, Nicholas Zolman, J. Nathan Kutz, Steven L. Brunton
2025	J	`jnl`	Accelerating scientific discovery with the common task framework. CoRR J. Nathan Kutz, Peter W. Battaglia, Michael P. Brenner, Kevin Carlberg, Aric A. Hagberg, Shirley Ho, Stephan Hoyer, Henning Lange, Hod Lipson, Michael W. Mahoney, Frank Noé, Max Welling, Laure Zanna, Francis Zhu, Steven L. Brunton
2025	J	`jnl`	Arousal as a universal embedding for spatiotemporal brain dynamics. Nat. Ryan V. Raut, Zachary P. Rosenthal, Xiaodan Wang, Hanyang Miao, Zhanqi Zhang, Jin-Moo Lee, Marcus E. Raichle, Adam Q. Bauer, Steven L. Brunton, Bingni W. Brunton, J. Nathan Kutz
2025	—	`conf`	Controlling chaotic energy events in fluids with reinforcement learning. e-Energy Sajeda Mokbel, Christian Lagemann, Esther Lagemann, Steven L. Brunton
2025	J	`jnl`	From STLS to Projection-based Dictionary Selection in Sparse Regression for System Identification. CoRR Hangjun Cho, Fabio Amaral, Andrei A. Klishin, Cassio M. Oishi, Steven L. Brunton
2025	—	`conf`	HydroGym: A Reinforcement Learning Platform for Fluid Dynamics. L4DC Christian Lagemann, Ludger Paehler, Jared Callaham, Sajeda Mokbel, Samuel Ahnert, Kai Lagemann, Esther Lagemann, Nikolaus A. Adams, Steven L. Brunton
2025	J	`jnl`	HydroGym: A Reinforcement Learning Platform for Fluid Dynamics. CoRR Christian Lagemann, Sajeda Mokbel, Miro Gondrum, Mario Rüttgers, Jared Callaham, Ludger Paehler, Samuel Ahnert, Nicholas Zolman, Kai Lagemann, Nikolaus A. Adams, Matthias Meinke, Wolfgang Schröder, Jean-Christophe Loiseau, Esther Lagemann, Steven L. Brunton
2025	J	`jnl`	Machine Learning for Sparse Nonlinear Modeling and Control. Annu. Rev. Control. Robotics Auton. Syst. Steven L. Brunton, Nicholas Zolman, J. Nathan Kutz, Urban Fasel
2025	J	`jnl`	Meshless projection model-order reduction via reference spaces for smoothed-particle hydrodynamics. CoRR Steven N. Rodriguez, Steven L. Brunton, Liam K. Magargal, Parisa Khodabakshi, Justin W. Jaworski, Nicole A. Apetre, John C. Steuben, John G. Michopoulos, Athanasios Iliopoulos
2025	—	`conf`	Physics-Enforced Reservoir Computing for Forecasting Spatiotemporal Systems. L4DC Dima Tretiak, Anastasia S. Bizyaeva, J. Nathan Kutz, Steven L. Brunton
2025	J	`jnl`	PySensors 2.0: A Python Package for Sparse Sensor Placement. CoRR Niharika Karnik, Yash Bhangale, Mohammad G. Abdo, Andrei A. Klishin, Joshua J. Cogliati, Bingni W. Brunton, J. Nathan Kutz, Steven L. Brunton, Krithika Manohar
2025	J	`jnl`	Reduced-order modeling and classification of hydrodynamic pattern formation in gravure printing. CoRR Pauline Rothmann-Brumm, Steven L. Brunton, Isabel Scherl
2025	J	`jnl`	Safe Physics-Informed Machine Learning for Dynamics and Control. CoRR Ján Drgona, Truong X. Nghiem, Thomas Beckers, Mahyar Fazlyab, Enrique Mallada, Colin N. Jones, Draguna L. Vrabie, Steven L. Brunton, Rolf Findeisen
2025	C	`conf`	Safe Physics-informed Machine Learning for Dynamics and Control. ACC Ján Drgona, Truong X. Nghiem, Thomas Beckers, Mahyar Fazlyab, Enrique Mallada, Colin N. Jones, Draguna L. Vrabie, Steven L. Brunton, Rolf Findeisen
2025	J	`jnl`	Sparse-mode Dynamic Mode Decomposition for Disambiguating Local and Global Structures. CoRR Sara M. Ichinaga, Steven L. Brunton, Aleksandr Y. Aravkin, J. Nathan Kutz
2024	J	`jnl`	A deep learning approach to wall-shear stress quantification: From numerical training to zero-shot experimental application. CoRR Esther Lagemann, Julia Roeb, Steven L. Brunton, Christian Lagemann
2024	J	`jnl`	AI Institute in Dynamic Systems: Developing machine learning and AI tools for scientific discovery, engineering design, and data-driven control. AI Mag. J. Nathan Kutz, Steven L. Brunton, Krithika Manohar, Hod Lipson, Na Li
2024	J	`jnl`	Computed tomography using meta-optics. CoRR Maksym Zhelyeznuyakov, Johannes E. Fröch, Shane Colburn, Steven L. Brunton, Arka Majumdar
2024	J	`jnl`	Deep Generative Modeling for Identification of Noisy, Non-Stationary Dynamical Systems. CoRR Doris Voina, Steven L. Brunton, J. Nathan Kutz
2024	J	`jnl`	Estimating Dynamic Flow Features in Groups of Tracked Objects. CoRR Tanner D. Harms, Steven L. Brunton, Beverley J. McKeon
2024	J	`jnl`	Koopman-Assisted Reinforcement Learning. CoRR Preston Rozwood, Edward Mehrez, Ludger Paehler, Wen Sun, Steven L. Brunton
2024	J	`jnl`	Mobile Sensor Path Planning for Kalman Filter Spatiotemporal Estimation. Sensors Jiazhong Mei, Steven L. Brunton, J. Nathan Kutz
2024	J	`jnl`	Multi-Hierarchical Surrogate Learning for Structural Dynamical Crash Simulations Using Graph Convolutional Neural Networks. CoRR Jonas Kneifl, Jörg Fehr, Steven L. Brunton, J. Nathan Kutz
2024	J	`jnl`	Opportunities for machine learning in scientific discovery. CoRR Ricardo Vinuesa, Jean Rabault, Hossein Azizpour, Stefan Bauer, Bingni W. Brunton, Arne Elofsson, Elias Jarlebring, Hedvig Kjellström, Stefano Markidis, David Marlevi, Paola Cinnella, Steven L. Brunton
2024	J	`jnl`	Promising directions of machine learning for partial differential equations. Nat. Comput. Sci. Steven L. Brunton, J. Nathan Kutz
2024	J	`jnl`	PyDMD: A Python Package for Robust Dynamic Mode Decomposition. J. Mach. Learn. Res. Sara M. Ichinaga, Francesco Andreuzzi, Nicola Demo, Marco Tezzele, Karl Lapo, Gianluigi Rozza, Steven L. Brunton, J. Nathan Kutz
2024	J	`jnl`	PyDMD: A Python package for robust dynamic mode decomposition. CoRR Sara M. Ichinaga, Francesco Andreuzzi, Nicola Demo, Marco Tezzele, Karl Lapo, Gianluigi Rozza, Steven L. Brunton, J. Nathan Kutz
2024	J	`jnl`	PyKoopman: A Python Package for Data-Driven Approximation of the Koopman Operator. J. Open Source Softw. Shaowu Pan, Eurika Kaiser, Brian M. de Silva, J. Nathan Kutz, Steven L. Brunton
2024	J	`jnl`	SINDy-RL: Interpretable and Efficient Model-Based Reinforcement Learning. CoRR Nicholas Zolman, Urban Fasel, J. Nathan Kutz, Steven L. Brunton
2024	Misc	`conf`	Single-Pixel Imaging Of Dynamic Flows Using Neural Ode Regularization. ICASSP Aleksei Sholokhov, Joshua Rapp, Saleh Nabi, Steven L. Brunton, J. Nathan Kutz, Hassan Mansour
2024	J	`jnl`	Single-Pixel Imaging of Spatio-Temporal Flows Using Differentiable Latent Dynamics. IEEE Trans. Computational Imaging Aleksei Sholokhov, Saleh Nabi, Joshua Rapp, Steven L. Brunton, J. Nathan Kutz, Petros T. Boufounos, Hassan Mansour
2024	J	`jnl`	VENI, VINDy, VICI: a variational reduced-order modeling framework with uncertainty quantification. CoRR Paolo Conti, Jonas Kneifl, Andrea Manzoni, Attilio Frangi, Jörg Fehr, Steven L. Brunton, J. Nathan Kutz
2023	J	`jnl`	A Unified Framework to Enforce, Discover, and Promote Symmetry in Machine Learning. CoRR Samuel E. Otto, Nicholas Zolman, J. Nathan Kutz, Steven L. Brunton
2023	J	`jnl`	Benchmarking sparse system identification with low-dimensional chaos. CoRR Alan A. Kaptanoglu, Lanyue Zhang, Zachary G. Nicolaou, Urban Fasel, Steven L. Brunton
2023	J	`jnl`	Control of Vortex Dynamics using Invariants. CoRR Kartik Krishna, Aditya G. Nair, Anand Krishnan, Steven L. Brunton, Eurika Kaiser
2023	J	`jnl`	Convergence of uncertainty estimates in Ensemble and Bayesian sparse model discovery. CoRR L. Mars Gao, Urban Fasel, Steven L. Brunton, J. Nathan Kutz
2023	C	`conf`	Data-Driven Control: Theory and Applications. ACC Damoon Soudbakhsh, Anuradha M. Annaswamy, Yan Wang, Steven L. Brunton, Joseph E. Gaudio, Heather S. Hussain, Draguna L. Vrabie, Ján Drgona, Dimitar P. Filev
2023	J	`jnl`	Data-driven prediction of the performance of enhanced surfaces from an extensive CFD-generated parametric search space. Mach. Learn. Sci. Technol. Ana Larrañaga, Steven L. Brunton, Javier Martínez, Sergio Chapela, Jacobo Porteiro
2023	J	`jnl`	Distributed Control of Partial Differential Equations Using Convolutional Reinforcement Learning. CoRR Sebastian Peitz, Jan Stenner, Vikas Chidananda, Oliver Wallscheid, Steven L. Brunton, Kunihiko Taira
2023	J	`jnl`	Finite Time Lyapunov Exponent Analysis of Model Predictive Control and Reinforcement Learning. IEEE Access Kartik Krishna, Steven L. Brunton, Zhuoyuan Song
2023	J	`jnl`	Finite Time Lyapunov Exponent Analysis of Model Predictive Control and Reinforcement Learning. CoRR Kartik Krishna, Steven L. Brunton, Zhuoyuan Song
2023	J	`jnl`	HyperSINDy: Deep Generative Modeling of Nonlinear Stochastic Governing Equations. CoRR Mozes Jacobs, Bingni W. Brunton, Steven L. Brunton, J. Nathan Kutz, Ryan V. Raut
2023	J	`jnl`	Machine Learning for Partial Differential Equations. CoRR Steven L. Brunton, J. Nathan Kutz
2023	J	`jnl`	Multi-fidelity reduced-order surrogate modeling. CoRR Paolo Conti, Mengwu Guo, Andrea Manzoni, Attilio Frangi, Steven L. Brunton, J. Nathan Kutz
2023	J	`jnl`	Multiresolution convolutional autoencoders. J. Comput. Phys. Yuying Liu, Colin Ponce, Steven L. Brunton, J. Nathan Kutz
2023	J	`jnl`	Neural Implicit Flow: a mesh-agnostic dimensionality reduction paradigm of spatio-temporal data. J. Mach. Learn. Res. Shaowu Pan, Steven L. Brunton, J. Nathan Kutz
2023	J	`jnl`	Nonlinear parametric models of viscoelastic fluid flows. CoRR Cassio M. Oishi, Alan A. Kaptanoglu, J. Nathan Kutz, Steven L. Brunton
2023	—	`conf`	Observability-Based Energy Efficient Path Planning with Background Flow via Deep Reinforcement Learning. CDC Jiazhong Mei, J. Nathan Kutz, Steven L. Brunton
2023	J	`jnl`	Optimal Sensor Placement with Adaptive Constraints for Nuclear Digital Twins. CoRR Niharika Karnik, Mohammad G. Abdo, Carlos E. Estrada Perez, Jun Soo Yoo, Joshua J. Cogliati, Richard S. Skifton, Pattrick Calderoni, Steven L. Brunton, Krithika Manohar
2023	J	`jnl`	PyKoopman: A Python Package for Data-Driven Approximation of the Koopman Operator. CoRR Shaowu Pan, Eurika Kaiser, Brian M. de Silva, J. Nathan Kutz, Steven L. Brunton
2023	A*	`conf`	Robust, High-Rate Trajectory Tracking on Insect-Scale Soft-Actuated Aerial Robots with Deep-Learned Tube MPC. ICRA Andrea Tagliabue, Yi-Hsuan Hsiao, Urban Fasel, J. Nathan Kutz, Steven L. Brunton, YuFeng Chen, Jonathan P. How
2023	J	`jnl`	The transformative potential of machine learning for experiments in fluid mechanics. CoRR Ricardo Vinuesa, Steven L. Brunton, Beverley J. McKeon
2023	J	`jnl`	Uncovering wall-shear stress dynamics from neural-network enhanced fluid flow measurements. CoRR Esther Lagemann, Steven L. Brunton, Christian Lagemann
2022	J	`jnl`	Automatic differentiation to simultaneously identify nonlinear dynamics and extract noise probability distributions from data. Mach. Learn. Sci. Technol. Kadierdan Kaheman, Steven L. Brunton, J. Nathan Kutz
2022	J	`jnl`	Bounded nonlinear forecasts of partially observed geophysical systems with physics-constrained deep learning. CoRR Said Ouala, Steven L. Brunton, Ananda Pascual, Bertrand Chapron, Fabrice Collard, Lucile Gaultier, Ronan Fablet
2022	J	`jnl`	Deeptime: a Python library for machine learning dynamical models from time series data. Mach. Learn. Sci. Technol. Moritz Hoffmann, Martin Scherer, Tim Hempel, Andreas Mardt, Brian de Silva, Brooke E. Husic, Stefan Klus, Hao Wu, J. Nathan Kutz, Steven L. Brunton, Frank Noé
2022	J	`jnl`	Dimensionally Consistent Learning with Buckingham Pi. CoRR Joseph Bakarji, Jared Callaham, Steven L. Brunton, J. Nathan Kutz
2022	J	`jnl`	Dimensionally consistent learning with Buckingham Pi. Nat. Comput. Sci. Joseph Bakarji, Jared Callaham, Steven L. Brunton, J. Nathan Kutz
2022	J	`jnl`	Discovering Governing Equations from Partial Measurements with Deep Delay Autoencoders. CoRR Joseph Bakarji, Kathleen P. Champion, J. Nathan Kutz, Steven L. Brunton
2022	J	`jnl`	Emerging Trends in Machine Learning for Computational Fluid Dynamics. Comput. Sci. Eng. Ricardo Vinuesa, Steven L. Brunton
2022	J	`jnl`	Emerging trends in machine learning for computational fluid dynamics. CoRR Ricardo Vinuesa, Steven L. Brunton
2022	J	`jnl`	Enhancing computational fluid dynamics with machine learning. Nat. Comput. Sci. Ricardo Vinuesa, Steven L. Brunton
2022	J	`jnl`	FlexWing-ROM: A matlab framework for data-driven reduced-order modeling of flexible wings. J. Open Source Softw. Urban Fasel, Nicola Fonzi, Andrea Iannelli, Steven L. Brunton
2022	J	`jnl`	Model predictive control for robust quantum state preparation. Quantum Andy Goldschmidt, Jonathan L. Dubois, Steven L. Brunton, J. Nathan Kutz
2022	J	`jnl`	Modern Koopman Theory for Dynamical Systems. SIAM Rev. Steven L. Brunton, Marko Budisic, Eurika Kaiser, J. Nathan Kutz
2022	J	`jnl`	Neural Implicit Flow: a mesh-agnostic dimensionality reduction paradigm of spatio-temporal data. CoRR Shaowu Pan, Steven L. Brunton, J. Nathan Kutz
2022	—	`conf`	Nonlinear System Level Synthesis for Polynomial Dynamical Systems. CDC Lauren E. Conger, Jing Shuang Lisa Li, Eric Mazumdar, Steven L. Brunton
2022	J	`jnl`	Optimal Sensor and Actuator Selection Using Balanced Model Reduction. IEEE Trans. Autom. Control. Krithika Manohar, J. Nathan Kutz, Steven L. Brunton
2022	J	`jnl`	Projection-tree reduced-order modeling for fast J. Comput. Phys. Steven N. Rodriguez, Athanasios P. Iliopoulos, Kevin T. Carlberg, Steven L. Brunton, John C. Steuben, John G. Michopoulos
2022	J	`jnl`	PySINDy: A comprehensive Python package for robust sparse system identification. J. Open Source Softw. Alan A. Kaptanoglu, Brian de Silva, Urban Fasel, Kadierdan Kaheman, Andy Goldschmidt, Jared Callaham, Charles B. Delahunt, Zachary Nicolaou, Kathleen P. Champion, Jean-Christophe Loiseau, J. Nathan Kutz, Steven L. Brunton
2022	J	`jnl`	Robust, High-Rate Trajectory Tracking on Insect-Scale Soft-Actuated Aerial Robots with Deep-Learned Tube MPC. CoRR Andrea Tagliabue, Yi-Hsuan Hsiao, Urban Fasel, J. Nathan Kutz, Steven L. Brunton, YuFeng Chen, Jonathan P. How
2022	J	`jnl`	Swarm Modeling With Dynamic Mode Decomposition. IEEE Access Emma Hansen, Steven L. Brunton, Zhuoyuan Song
2022	J	`jnl`	Swarm Modelling with Dynamic Mode Decomposition. CoRR Emma Hansen, Steven L. Brunton, Zhuoyuan Song
2022	J	`jnl`	The Experimental Multi-Arm Pendulum on a Cart: A Benchmark System for Chaos, Learning, and Control. CoRR Kadierdan Kaheman, Urban Fasel, Jason J. Bramburger, Benjamin Strom, J. Nathan Kutz, Steven L. Brunton
2021	J	`jnl`	Applying Machine Learning to Study Fluid Mechanics. CoRR Steven L. Brunton
2021	J	`jnl`	Data-Driven Stabilization of Periodic Orbits. IEEE Access Jason J. Bramburger, J. Nathan Kutz, Steven L. Brunton
2021	J	`jnl`	Data-driven discovery of Koopman eigenfunctions for control. Mach. Learn. Sci. Technol. Eurika Kaiser, J. Nathan Kutz, Steven L. Brunton
2021	J	`jnl`	Deep Learning of Conjugate Mappings. CoRR Jason J. Bramburger, Steven L. Brunton, J. Nathan Kutz
2021	J	`jnl`	DeepGreen: Deep Learning of Green's Functions for Nonlinear Boundary Value Problems. CoRR Craig R. Gin, Daniel E. Shea, Steven L. Brunton, J. Nathan Kutz
2021	J	`jnl`	Deeptime: a Python library for machine learning dynamical models from time series data. CoRR Moritz Hoffmann, Martin Scherer, Tim Hempel, Andreas Mardt, Brian de Silva, Brooke E. Husic, Stefan Klus, Hao Wu, J. Nathan Kutz, Steven L. Brunton, Frank Noé
2021	J	`jnl`	Ensemble-SINDy: Robust sparse model discovery in the low-data, high-noise limit, with active learning and control. CoRR Urban Fasel, J. Nathan Kutz, Bingni W. Brunton, Steven L. Brunton
2021	J	`jnl`	Extraction of Instantaneous Frequencies and Amplitudes in Nonstationary Time-Series Data. IEEE Access Daniel E. Shea, Rajiv Giridharagopal, David S. Ginger, Steven L. Brunton, J. Nathan Kutz
2021	J	`jnl`	Extraction of instantaneous frequencies and amplitudes in nonstationary time-series data. CoRR Daniel E. Shea, Rajiv Giridharagopal, David S. Ginger, Steven L. Brunton, J. Nathan Kutz
2021	J	`jnl`	Finite-Horizon, Energy-Optimal Trajectories in Unsteady Flows. CoRR Kartik Krishna, Zhuoyuan Song, Steven L. Brunton
2021	J	`jnl`	From Fourier to Koopman: Spectral Methods for Long-term Time Series Prediction. J. Mach. Learn. Res. Henning Lange, Steven L. Brunton, J. Nathan Kutz
2021	J	`jnl`	Learning normal form autoencoders for data-driven discovery of universal, parameter-dependent governing equations. CoRR Manu Kalia, Steven L. Brunton, Hil G. E. Meijer, Christoph Brune, J. Nathan Kutz
2021	J	`jnl`	Modern Koopman Theory for Dynamical Systems. CoRR Steven L. Brunton, Marko Budisic, Eurika Kaiser, J. Nathan Kutz
2021	J	`jnl`	Physics-informed dynamic mode decomposition (piDMD). CoRR Peter J. Baddoo, Benjamin Herrmann, Beverley J. McKeon, J. Nathan Kutz, Steven L. Brunton
2021	J	`jnl`	Projection-tree reduced order modeling for fast N-body computations. CoRR Steven N. Rodriguez, Athanasios P. Iliopoulos, Kevin T. Carlberg, Steven L. Brunton, John C. Steuben, John G. Michopoulos
2021	J	`jnl`	PySINDy: A comprehensive Python package for robust sparse system identification. CoRR Alan A. Kaptanoglu, Brian M. de Silva, Urban Fasel, Kadierdan Kaheman, Jared L. Callaham, Charles B. Delahunt, Kathleen P. Champion, Jean-Christophe Loiseau, J. Nathan Kutz, Steven L. Brunton
2021	J	`jnl`	PySensors: A Python Package for Sparse Sensor Placement. CoRR Brian M. de Silva, Krithika Manohar, Emily Clark, Bingni W. Brunton, Steven L. Brunton, J. Nathan Kutz
2021	J	`jnl`	PySensors: A Python package for sparse sensor placement. J. Open Source Softw. Brian M. de Silva, Krithika Manohar, Emily Clark, Bingni W. Brunton, J. Nathan Kutz, Steven L. Brunton
2021	—	`conf`	SINDy with Control: A Tutorial. CDC Urban Fasel, Eurika Kaiser, J. Nathan Kutz, Bingni W. Brunton, Steven L. Brunton
2021	J	`jnl`	The Potential of Machine Learning to Enhance Computational Fluid Dynamics. CoRR Ricardo Vinuesa, Steven L. Brunton
2020	J	`jnl`	A Unified Sparse Optimization Framework to Learn Parsimonious Physics-Informed Models From Data. IEEE Access Kathleen P. Champion, Peng Zheng, Aleksandr Y. Aravkin, Steven L. Brunton, J. Nathan Kutz
2020	J	`jnl`	Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributions from Data. CoRR Kadierdan Kaheman, Steven L. Brunton, J. Nathan Kutz
2020	J	`jnl`	Bracketing brackets with bras and kets. CoRR Emily Clark, Angelie Vincent, J. Nathan Kutz, Steven L. Brunton
2020	J	`jnl`	Data-Driven Aerospace Engineering: Reframing the Industry with Machine Learning. CoRR Steven L. Brunton, J. Nathan Kutz, Krithika Manohar, Aleksandr Y. Aravkin, Kristi Morgansen, Jennifer Klemisch, Nicholas Goebel, James Buttrick, Jeffrey Poskin, Agnes Blom-Schieber, Thomas A. Hogan, Darren McDonald
2020	J	`jnl`	Deep reinforcement learning for optical systems: A case study of mode-locked lasers. Mach. Learn. Sci. Technol. Chang Sun, Eurika Kaiser, Steven L. Brunton, J. Nathan Kutz
2020	J	`jnl`	Discovery of Physics From Data: Universal Laws and Discrepancies. Frontiers Artif. Intell. Brian de Silva, David M. Higdon, Steven L. Brunton, J. Nathan Kutz
2020	J	`jnl`	From Fourier to Koopman: Spectral Methods for Long-term Time Series Prediction. CoRR Henning Lange, Steven L. Brunton, J. Nathan Kutz
2020	J	`jnl`	Hierarchical Deep Learning of Multiscale Differential Equation Time-Steppers. CoRR Yuying Liu, J. Nathan Kutz, Steven L. Brunton
2020	J	`jnl`	Learning Precisely Timed Feedforward Control of the Sensor-Denied Inverted Pendulum. IEEE Control. Syst. Lett. Thomas L. Mohren, Thomas L. Daniel, Steven L. Brunton
2020	J	`jnl`	Multiresolution Convolutional Autoencoders. CoRR Yuying Liu, Colin Ponce, Steven L. Brunton, J. Nathan Kutz
2020	J	`jnl`	Physics-informed machine learning for sensor fault detection with flight test data. CoRR Brian M. de Silva, Jared Callaham, Jonathan Jonker, Nicholas Goebel, Jennifer Klemisch, Darren McDonald, Nathan Hicks, J. Nathan Kutz, Steven L. Brunton, Aleksandr Y. Aravkin
2020	J	`jnl`	Principal Component Trajectories (PCT): Nonlinear dynamics as a superposition of time-delayed periodic orbits. CoRR Daniel Dylewsky, Eurika Kaiser, Steven L. Brunton, J. Nathan Kutz
2020	J	`jnl`	PySINDy: A Python package for the sparse identification of nonlinear dynamical systems from data. J. Open Source Softw. Brian de Silva, Kathleen P. Champion, Markus Quade, Jean-Christophe Loiseau, J. Nathan Kutz, Steven L. Brunton
2020	J	`jnl`	Randomized CP tensor decomposition. Mach. Learn. Sci. Technol. N. Benjamin Erichson, Krithika Manohar, Steven L. Brunton, J. Nathan Kutz
2020	J	`jnl`	SINDy-BVP: Sparse Identification of Nonlinear Dynamics for Boundary Value Problems. CoRR Daniel E. Shea, Steven L. Brunton, J. Nathan Kutz
2020	J	`jnl`	SINDy-PI: A Robust Algorithm for Parallel Implicit Sparse Identification of Nonlinear Dynamics. CoRR Kadierdan Kaheman, J. Nathan Kutz, Steven L. Brunton
2020	J	`jnl`	Sparse Principal Component Analysis via Variable Projection. SIAM J. Appl. Math. N. Benjamin Erichson, Peng Zheng, Krithika Manohar, Steven L. Brunton, J. Nathan Kutz, Aleksandr Y. Aravkin
2020	J	`jnl`	Time-Delay Observables for Koopman: Theory and Applications. SIAM J. Appl. Dyn. Syst. Mason Kamb, Eurika Kaiser, Steven L. Brunton, J. Nathan Kutz
2019	J	`jnl`	A Unified Framework for Sparse Relaxed Regularized Regression: SR3. IEEE Access Peng Zheng, Travis Askham, Steven L. Brunton, J. Nathan Kutz, Aleksandr Y. Aravkin
2019	J	`jnl`	A unified sparse optimization framework to learn parsimonious physics-informed models from data. CoRR Kathleen P. Champion, Peng Zheng, Aleksandr Y. Aravkin, Steven L. Brunton, J. Nathan Kutz
2019	J	`jnl`	Compressed dynamic mode decomposition for background modeling. J. Real Time Image Process. N. Benjamin Erichson, Steven L. Brunton, J. Nathan Kutz
2019	J	`jnl`	Data-Driven Identification of Parametric Partial Differential Equations. SIAM J. Appl. Dyn. Syst. Samuel H. Rudy, Alessandro Alla, Steven L. Brunton, J. Nathan Kutz
2019	J	`jnl`	Deep Learning Models for Global Coordinate Transformations that Linearize PDEs. CoRR Craig Gin, Bethany Lusch, Steven L. Brunton, J. Nathan Kutz
2019	J	`jnl`	Deep Model Predictive Control with Online Learning for Complex Physical Systems. CoRR Katharina Bieker, Sebastian Peitz, Steven L. Brunton, J. Nathan Kutz, Michael Dellnitz
2019	J	`jnl`	Deep learning of dynamics and signal-noise decomposition with time-stepping constraints. J. Comput. Phys. Samuel H. Rudy, J. Nathan Kutz, Steven L. Brunton
2019	J	`jnl`	Discovery of Nonlinear Multiscale Systems: Sampling Strategies and Embeddings. SIAM J. Appl. Dyn. Syst. Kathleen P. Champion, Steven L. Brunton, J. Nathan Kutz
2019	J	`jnl`	Discovery of Physics from Data: Universal Laws and Discrepancy Models. CoRR Brian de Silva, David M. Higdon, Steven L. Brunton, J. Nathan Kutz
2019	J	`jnl`	Learning Discrepancy Models From Experimental Data. CoRR Kadierdan Kaheman, Eurika Kaiser, Benjamin Strom, J. Nathan Kutz, Steven L. Brunton
2019	J	`jnl`	Learning Precisely Timed Feedforward Control of the Sensor-Denied Inverted Pendulum. CoRR Thomas L. Mohren, Thomas L. Daniel, Steven L. Brunton
2019	J	`jnl`	Machine Learning for Fluid Mechanics. CoRR Steven L. Brunton, Bernd Noack, Petros Koumoutsakos
2019	J	`jnl`	Optimized Sampling for Multiscale Dynamics. Multiscale Model. Simul. Krithika Manohar, Eurika Kaiser, Steven L. Brunton, J. Nathan Kutz
2019	J	`jnl`	Randomized Dynamic Mode Decomposition. SIAM J. Appl. Dyn. Syst. N. Benjamin Erichson, Lionel Mathelin, J. Nathan Kutz, Steven L. Brunton
2019	J	`jnl`	Randomized methods to characterize large-scale vortical flow network. CoRR Zhe Bai, N. Benjamin Erichson, Muralikrishnan Gopalakrishnan Meena, Kunihiko Taira, Steven L. Brunton
2019	J	`jnl`	RetinaMatch: Efficient Template Matching of Retina Images for Teleophthalmology. IEEE Trans. Medical Imaging Chen Gong, N. Benjamin Erichson, John P. Kelly, Laura C. Trutoiu, Brian T. Schowengerdt, Steven L. Brunton, Eric J. Seibel
2019	J	`jnl`	Shallow Learning for Fluid Flow Reconstruction with Limited Sensors and Limited Data. CoRR N. Benjamin Erichson, Lionel Mathelin, Zhewei Yao, Steven L. Brunton, Michael W. Mahoney, J. Nathan Kutz
2019	J	`jnl`	Smoothing and parameter estimation by soft-adherence to governing equations. J. Comput. Phys. Samuel H. Rudy, Steven L. Brunton, J. Nathan Kutz
2018	J	`jnl`	Applied Koopman Theory for Partial Differential Equations and Data-Driven Modeling of Spatio-Temporal Systems. Complex. J. Nathan Kutz, Joshua L. Proctor, Steven L. Brunton
2018	J	`jnl`	Diffusion Maps meet Nyström. CoRR N. Benjamin Erichson, Lionel Mathelin, Steven L. Brunton, J. Nathan Kutz
2018	—	`conf`	Discovering Conservation Laws from Data for Control. CDC Eurika Kaiser, J. Nathan Kutz, Steven L. Brunton
2018	J	`jnl`	Discovering conservation laws from data for control. CoRR Eurika Kaiser, J. Nathan Kutz, Steven L. Brunton
2018	J	`jnl`	Generalizing Koopman Theory to Allow for Inputs and Control. SIAM J. Appl. Dyn. Syst. Joshua L. Proctor, Steven L. Brunton, J. Nathan Kutz
2018	J	`jnl`	Online Interpolation Point Refinement for Reduced-Order Models using a Genetic Algorithm. SIAM J. Sci. Comput. Syuzanna Sargsyan, Steven L. Brunton, J. Nathan Kutz
2018	J	`jnl`	Optimal Sensor and Actuator Placement using Balanced Model Reduction. CoRR Krithika Manohar, J. Nathan Kutz, Steven L. Brunton
2018	J	`jnl`	RetinaMatch: Efficient Template Matching of Retina Images for Teleophthalmology. CoRR Chen Gong, N. Benjamin Erichson, John P. Kelly, Laura C. Trutoiu, Brian T. Schowengerdt, Steven L. Brunton, Eric J. Seibel
2018	J	`jnl`	Sparse Principal Component Analysis via Variable Projection. CoRR N. Benjamin Erichson, Peng Zeng, Krithika Manohar, Steven L. Brunton, J. Nathan Kutz, Aleksandr Y. Aravkin
2018	J	`jnl`	Sparse Relaxed Regularized Regression: SR3. CoRR Peng Zheng, Travis Askham, Steven L. Brunton, J. Nathan Kutz, Aleksandr Y. Aravkin
2018	J	`jnl`	Sparse-TDA: Sparse Realization of Topological Data Analysis for Multi-Way Classification. IEEE Trans. Knowl. Data Eng. Wei Guo, Krithika Manohar, Steven L. Brunton, Ashis Gopal Banerjee
2018	J	`jnl`	Sparsity enabled cluster reduced-order models for control. J. Comput. Phys. Eurika Kaiser, Marek Morzynski, Guillaume Daviller, J. Nathan Kutz, Bingni W. Brunton, Steven L. Brunton
2017	—	`conf`	Compressed Singular Value Decomposition for Image and Video Processing. ICCV Workshops N. Benjamin Erichson, Steven L. Brunton, J. Nathan Kutz
2017	J	`jnl`	Data-Driven Sparse Sensor Placement. CoRR Krithika Manohar, Bingni W. Brunton, J. Nathan Kutz, Steven L. Brunton
2017	—	`conf`	Data-Driven discovery of governing physical laws and their parametric dependencies in engineering, physics and biology. CAMSAP J. Nathan Kutz, Samuel H. Rudy, Alessandro Alla, Steven L. Brunton
2017	J	`jnl`	Deep Learning and Model Predictive Control for Self-Tuning Mode-Locked Lasers. CoRR Thomas Baumeister, Steven L. Brunton, J. Nathan Kutz
2017	J	`jnl`	Deep learning for universal linear embeddings of nonlinear dynamics. CoRR Bethany Lusch, J. Nathan Kutz, Steven L. Brunton
2017	—	`conf`	Dynamic Mode Decomposition for Background Modeling. ICCV Workshops Seth D. Pendergrass, Steven L. Brunton, J. Nathan Kutz, N. Benjamin Erichson, Travis Askham
2017	J	`jnl`	Dynamic mode decomposition for compressive system identification. CoRR Zhe Bai, Eurika Kaiser, Joshua L. Proctor, J. Nathan Kutz, Steven L. Brunton
2017	J	`jnl`	Randomized CP Tensor Decomposition. CoRR N. Benjamin Erichson, Krithika Manohar, Steven L. Brunton, J. Nathan Kutz
2017	J	`jnl`	Randomized Dynamic Mode Decomposition. CoRR N. Benjamin Erichson, Steven L. Brunton, J. Nathan Kutz
2017	J	`jnl`	Sparse-TDA: Sparse Realization of Topological Data Analysis for Multi-Way Classification. CoRR Wei Guo, Krithika Manohar, Steven L. Brunton, Ashis Gopal Banerjee
2017	J	`jnl`	Spatiotemporal Feedback and Network Structure Drive and Encode Caenorhabditis elegans Locomotion. PLoS Comput. Biol. James M. Kunert, Joshua L. Proctor, Steven L. Brunton, J. Nathan Kutz
2016	J	`jnl`	Dynamic Mode Decomposition with Control. SIAM J. Appl. Dyn. Syst. Joshua L. Proctor, Steven L. Brunton, J. Nathan Kutz
2016	—	`book`	Dynamic mode decomposition - data-driven modeling of complex systems. J. Nathan Kutz, Steven L. Brunton, Bingni W. Brunton, Joshua L. Proctor
2016	J	`jnl`	Inferring Biological Networks by Sparse Identification of Nonlinear Dynamics. IEEE Trans. Mol. Biol. Multi Scale Commun. Niall M. Mangan, Steven L. Brunton, Joshua L. Proctor, J. Nathan Kutz
2016	J	`jnl`	Multiresolution Dynamic Mode Decomposition. SIAM J. Appl. Dyn. Syst. J. Nathan Kutz, Xing Fu, Steven L. Brunton
2016	J	`jnl`	Online interpolation point refinement for reduced order models using a genetic algorithm. CoRR Syuzanna Sargsyan, Steven L. Brunton, J. Nathan Kutz
2016	J	`jnl`	Randomized Matrix Decompositions using R. CoRR N. Benjamin Erichson, Sergey Voronin, Steven L. Brunton, J. Nathan Kutz
2016	J	`jnl`	Sparse Sensor Placement Optimization for Classification. SIAM J. Appl. Math. Bingni W. Brunton, Steven L. Brunton, Joshua L. Proctor, J. Nathan Kutz
2016	J	`jnl`	Streaming GPU Singular Value and Dynamic Mode Decompositions. CoRR Seth D. Pendergrass, J. Nathan Kutz, Steven L. Brunton
2015	J	`jnl`	Compressed Dynamic Mode Decomposition for Real-Time Object Detection. CoRR N. Benjamin Erichson, Steven L. Brunton, J. Nathan Kutz
2015	—	`conf`	Multi-resolution Dynamic Mode Decomposition for Foreground/Background Separation and Object Tracking. ICCV Workshops J. Nathan Kutz, Xing Fu, Steven L. Brunton, N. Benjamin Erichson
2014	J	`jnl`	Compressive Sensing and Low-Rank Libraries for Classification of Bifurcation Regimes in Nonlinear Dynamical Systems. SIAM J. Appl. Dyn. Syst. Steven L. Brunton, Jonathan H. Tu, Ido Bright, J. Nathan Kutz
2014	J	`jnl`	Long-time uncertainty propagation using generalized polynomial chaos and flow map composition. J. Comput. Phys. Dirk M. Luchtenburg, Steven L. Brunton, Clarence W. Rowley
2013	J	`jnl`	Optimal Sensor Placement and Enhanced Sparsity for Classification. CoRR Bingni W. Brunton, Steven L. Brunton, Joshua L. Proctor, J. Nathan Kutz