Steven L. Brunton
- Machine Learning for Fluid Mechanics
2019/09/12 by Steven L. Brunton, Bernd R. Noack, Petros Koumoutsakos · 98 citations
Physics and Astronomy · Computer Science · Materials Science · #Model Reduction and Neural Networks #Generative Adversarial Networks and Image Synthesis #Machine Learning in Materials Science
- Closed-Loop Turbulence Control: Progress and Challenges
2015/07/30 by Steven L. Brunton, Bernd R. Noack · 53 citations
Physics and Astronomy · Engineering · #Model Reduction and Neural Networks #Fluid Dynamics and Turbulent Flows #Aerodynamics and Acoustics in Jet Flows
- Modern Koopman Theory for Dynamical Systems
2022/05/01 by Steven L. Brunton, Marko Budišić, Eurika Kaiser +1 · 92 citations
Physics and Astronomy · Engineering · #Model Reduction and Neural Networks #Fluid Dynamics and Turbulent Flows #Fluid Dynamics and Vibration Analysis
- Modern Koopman Theory for Dynamical Systems
2021/02/24 by Steven L. Brunton, Marko Budišić, Brunton, Steven L. +5 · 68 citations
Physics and Astronomy · Engineering · #Model Reduction and Neural Networks #Fluid Dynamics and Turbulent Flows #Power System Optimization and Stability
- Dynamic mode decomposition with control
2014/09/22 by Joshua L. Proctor, Steven L. Brunton, Proctor, Joshua L. +3 · 33 citations
Physics and Astronomy · Engineering · #Model Reduction and Neural Networks #Machine Fault Diagnosis Techniques #Structural Health Monitoring Techniques
- Modal Analysis of Fluid Flows: An Overview
2017/02/05 by Kunihiko Taira, Taira, Kunihiko, Steven L. Brunton +17 · 32 citations
Engineering · Physics and Astronomy · #FOS: Physical sciences #Fluid Dynamics (physics.flu-dyn) #Fluid Dynamics and Turbulent Flows #Fluid Dynamics and Vibration Analysis #Model Reduction and Neural Networks
- PySINDy: A Python package for the Sparse Identification of Nonlinear Dynamics from Data
2020/04/17 by Brian M. de Silva, de Silva, Brian M., Kathleen Champion +9 · 1 voice · 6 citations
Computer Science · Engineering · Mathematics · Physics and Astronomy · #Computational Physics (physics.comp-ph) #Computational Physics and Python Applications #Dynamical Systems (math.DS) #FOS: Mathematics #FOS: Physical sciences #Fluid Dynamics and Turbulent Flows #Model Reduction and Neural Networks #math.DS #physics.comp-ph
- A unified sparse optimization framework to learn parsimonious\n physics-informed models from data
2019/06/25 by Kathleen M. Champion, Champion, Kathleen, Peng Zheng +7 · 16 citations
Computer Science · Materials Science · Physics and Astronomy · #Computational Physics (physics.comp-ph) #FOS: Computer and information sciences #FOS: Physical sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning in Materials Science #Model Reduction and Neural Networks
- Modal Analysis of Fluid Flows: Applications and Outlook
2019/03/13 by Kunihiko Taira, Maziar S. Hemati, Taira, Kunihiko +13 · 11 citations
Engineering · Physics and Astronomy · #FOS: Physical sciences #Fluid Dynamics (physics.flu-dyn) #Fluid Dynamics and Turbulent Flows #Fluid Dynamics and Vibration Analysis #Model Reduction and Neural Networks
- A Unified Framework for Sparse Relaxed Regularized Regression: SR3
2018/07/14 by Peng Zheng, Zheng, Peng, Travis Askham +7 · 9 citations
Engineering · Mathematics · #49M15 #62F35 #65K10 #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Microwave Imaging and Scattering Analysis #Numerical methods in inverse problems #Optimization and Control (math.OC) #Sparse and Compressive Sensing Techniques
- Multi-Resolution Dynamic Mode Decomposition
2015/06/01 by J. Nathan Kutz, Xing Fu, Kutz, J. Nathan +3 · 7 citations
Earth and Planetary Sciences · Engineering · Physics and Astronomy · #Dynamical Systems (math.DS) #FOS: Mathematics #Machine Fault Diagnosis Techniques #Model Reduction and Neural Networks #Seismic Imaging and Inversion Techniques
- Data-Driven Aerospace Engineering: Reframing the Industry with Machine Learning
2021/07/20 by Steven L. Brunton, J. Nathan Kutz, Krithika Manohar +11 · 10 citations
Computer Science · Decision Sciences · Physics and Astronomy · #Advanced Multi-Objective Optimization Algorithms #Probabilistic and Robust Engineering Design #Model Reduction and Neural Networks
- Constrained Sparse Galerkin Regression
2016/11/10 by Jean-Christophe Loiseau, Loiseau, Jean-Christophe, Steven L. Brunton +1 · 6 citations
Physics and Astronomy · Engineering · Decision Sciences · #Model Reduction and Neural Networks #Fluid Dynamics and Vibration Analysis #Probabilistic and Robust Engineering Design
- SINDy with Control: A Tutorial
2021/08/30 by Urban Fasel, Fasel, Urban, Eurika Kaiser +7 · 8 citations
Physics and Astronomy · Engineering · #Model Reduction and Neural Networks #Control Systems and Identification #Fault Detection and Control Systems
- Discovering Governing Equations from Partial Measurements with Deep Delay Autoencoders
2022/01/13 by Joseph Bakarji, Bakarji, Joseph, Kathleen M. Champion +5 · 8 citations
Computer Science · Physics and Astronomy · #Computational Engineering #Dynamical Systems (math.DS) #FOS: Computer and information sciences #FOS: Mathematics #Finance #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Time Series Analysis and Forecasting #and Science (cs.CE)
- From Fourier to Koopman: Spectral Methods for Long-term Time Series Prediction
2020/04/01 by Henning Lange, Steven L. Brunton, Lange, Henning +3 · 6 citations
Decision Sciences · Engineering · Physics and Astronomy · #FOS: Computer and information sciences #FOS: Electrical engineering #Fluid Dynamics and Turbulent Flows #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks #Probabilistic and Robust Engineering Design #Signal Processing (eess.SP) #electronic engineering #information engineering
- Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributions from Data
2020/09/12 by Kadierdan Kaheman, Steven L. Brunton, Kaheman, Kadierdan +3 · 6 citations
Computer Science · Engineering · #93B30 #Anomaly Detection Techniques and Applications #Control Systems and Identification #Dynamical Systems (math.DS) #FOS: Computer and information sciences #FOS: Electrical engineering #FOS: Mathematics #Machine Learning (cs.LG) #Signal Processing (eess.SP) #Time Series Analysis and Forecasting #electronic engineering #information engineering
- Data-Driven Aerospace Engineering: Reframing the Industry with Machine\n Learning
2020/08/24 by Steven L. Brunton, J. Nathan Kutz, Brunton, Steven L. +21 · 5 citations
Computer Science · Engineering · Environmental Science · #Advanced Aircraft Design and Technologies #Advanced Multi-Objective Optimization Algorithms #FOS: Computer and information sciences #FOS: Electrical engineering #FOS: Mathematics #Machine Learning (cs.LG) #Optimization and Control (math.OC) #Radiative Heat Transfer Studies #Signal Processing (eess.SP) #electronic engineering #information engineering
- The transformative potential of machine learning for experiments in fluid mechanics
2023/03/28 by Ricardo Vinuesa, Vinuesa, Ricardo, Steven L. Brunton +3 · 7 citations
Engineering · Physics and Astronomy · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #FOS: Physical sciences #Fluid Dynamics (physics.flu-dyn) #Fluid Dynamics and Turbulent Flows #Lattice Boltzmann Simulation Studies #Model Reduction and Neural Networks
- Arousal as a universal embedding for spatiotemporal brain dynamics
2025/09/24 by Ryan V. Raut, Zachary P. Rosenthal, Xiaodan Wang +8 · 3 voices · 11 citations
Neuroscience · #Neural dynamics and brain function #Functional Brain Connectivity Studies #Memory and Neural Mechanisms
- A Unified Framework to Enforce, Discover, and Promote Symmetry in Machine Learning
2023/11/01 by Samuel E. Otto, Nicholas Zolman, Otto, Samuel E. +5 · 7 citations
Computer Science · Materials Science · Biochemistry, Genetics and Molecular Biology · #Computational Drug Discovery Methods #Machine Learning in Materials Science #Cell Image Analysis Techniques
- Multi-fidelity reduced-order surrogate modeling
2023/09/01 by Paolo Conti, Mengwu Guo, Conti, Paolo +9 · 7 citations
Engineering · Mathematics · Physics and Astronomy · #FOS: Computer and information sciences #FOS: Mathematics #Fluid Dynamics and Vibration Analysis #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Numerical Analysis (math.NA) #Numerical methods for differential equations
- Multiresolution Convolutional Autoencoders
2020/04/10 by Yuying Liu, Liu, Yuying, Colin Ponce +5 · 3 citations
Earth and Planetary Sciences · Physics and Astronomy · #Cryospheric studies and observations #FOS: Computer and information sciences #FOS: Electrical engineering #FOS: Mathematics #Image and Video Processing (eess.IV) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks #Numerical Analysis (math.NA) #Seismic Imaging and Inversion Techniques #electronic engineering #information engineering
- Hierarchical Deep Learning of Multiscale Differential Equation Time-Steppers
2020/08/22 by Yuying Liu, Liu, Yuying, J. Nathan Kutz +3 · 3 citations
Computer Science · Physics and Astronomy · #Computational Physics (physics.comp-ph) #FOS: Computer and information sciences #FOS: Mathematics #FOS: Physical sciences #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Neural Networks and Reservoir Computing #Numerical Analysis (math.NA)
- Finite Time Lyapunov Exponent Analysis of Model Predictive Control and Reinforcement Learning
2023/04/06 by Kartik Krishna, Krishna, Kartik, Steven L. Brunton +3 · 4 citations
Computer Science · Physics and Astronomy · #34D08 #34H05 #37D10 #37N10 #37N35 #76F25 #93B45 #Chaotic Dynamics (nlin.CD) #Distributed Control Multi-Agent Systems #Dynamical Systems (math.DS) #FOS: Computer and information sciences #FOS: Electrical engineering #FOS: Mathematics #FOS: Physical sciences #Model Reduction and Neural Networks #Optimization and Control (math.OC) #Reinforcement Learning in Robotics #Robotics (cs.RO) #Systems and Control (eess.SY) #electronic engineering #information engineering
- Challenges in Dynamic Mode Decomposition
2021/09/03 by Ziyou Wu, Steven L. Brunton, Wu, Ziyou +3 · 3 citations
Physics and Astronomy · Medicine · Engineering · #Model Reduction and Neural Networks #Cardiac electrophysiology and arrhythmias #Fluid Dynamics and Turbulent Flows
- Learning Discrepancy Models From Experimental Data
2019/09/18 by Kadierdan Kaheman, Eurika Kaiser, Kaheman, Kadierdan +7 · 3 citations
Physics and Astronomy · Engineering · #Model Reduction and Neural Networks #Hydraulic and Pneumatic Systems #Fault Detection and Control Systems
- An empirical mean-field model of symmetry-breaking in a turbulent wake
2021/05/28 by Jared Callaham, Callaham, Jared L., George Rigas +5 · 3 citations
Engineering · Environmental Science · #Fluid Dynamics and Vibration Analysis #Aerodynamics and Fluid Dynamics Research #Wind and Air Flow Studies
- PyKoopman: A Python Package for Data-Driven Approximation of the Koopman Operator
2023/06/22 by Shaowu Pan, Pan, Shaowu, Eurika Kaiser +7 · 4 citations
Engineering · Physics and Astronomy · #Computational Physics (physics.comp-ph) #Dynamical Systems (math.DS) #FOS: Computer and information sciences #FOS: Electrical engineering #FOS: Mathematics #FOS: Physical sciences #Fluid Dynamics and Turbulent Flows #Fluid Dynamics and Vibration Analysis #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Systems and Control (eess.SY) #electronic engineering #information engineering
- SINDy-RL: Interpretable and Efficient Model-Based Reinforcement Learning
2024/03/14 by Nicholas Zolman, Zolman, Nicholas, Urban Fasel +6 · 5 citations
Computer Science · #Reinforcement Learning in Robotics #Data Stream Mining Techniques #Anomaly Detection Techniques and Applications
- Convergence of uncertainty estimates in Ensemble and Bayesian sparse model discovery
2023/01/30 by Liyao Gao, Gao, L. Mars, Urban Fasel +5 · 4 citations
Chemistry · Computer Science · Engineering · #Dynamical Systems (math.DS) #FOS: Computer and information sciences #FOS: Mathematics #Fault Detection and Control Systems #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Methodology (stat.ME) #Spectroscopy and Chemometric Analyses
- Benchmarking sparse system identification with low-dimensional chaos
2023/02/04 by Alan A. Kaptanoglu, Kaptanoglu, Alan A., Lanyue Zhang +7 · 3 citations
Computer Science · Physics and Astronomy · #Anomaly Detection Techniques and Applications #Data Analysis #FOS: Computer and information sciences #FOS: Electrical engineering #FOS: Physical sciences #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Neural Networks and Applications #Statistics and Probability (physics.data-an) #Systems and Control (eess.SY) #electronic engineering #information engineering
- Learning normal form autoencoders for data-driven discovery of universal,parameter-dependent governing equations
2021/06/09 by Manu Kalia, Kalia, Manu, Steven L. Brunton +7 · 2 citations
Decision Sciences · Engineering · Physics and Astronomy · #37G05 #Dynamical Systems (math.DS) #FOS: Computer and information sciences #FOS: Mathematics #Fluid Dynamics and Turbulent Flows #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Probabilistic and Robust Engineering Design
- Constrained optimization of sensor placement for nuclear digital twins
2023/06/23 by Niharika Karnik, Karnik, Niharika, Mohammad Abdo +15 · 3 citations
Engineering · Materials Science · #Advanced Semiconductor Detectors and Materials #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning in Materials Science #Optimization and Control (math.OC) #Radiation Effects in Electronics
- The Experimental Multi-Arm Pendulum on a Cart: A Benchmark System for Chaos, Learning, and Control
2022/05/12 by Kadierdan Kaheman, Urban Fasel, Kaheman, Kadierdan +9 · 2 citations
Physics and Astronomy · #Experimental and Theoretical Physics Studies
- Multi-fidelity sensor selection: Greedy algorithms to place cheap and\n expensive sensors with cost constraints
2020/05/07 by Emily Clark, Clark, Emily, Steven L. Brunton +3 · 2 citations
Decision Sciences · Engineering · #Advanced Statistical Process Monitoring #FOS: Electrical engineering #Fault Detection and Control Systems #Scientific Measurement and Uncertainty Evaluation #Signal Processing (eess.SP) #electronic engineering #information engineering
- Nonlinear parametric models of viscoelastic fluid flows
2023/08/08 by Cássio M. Oishi, Oishi, Cassio M., Alan A. Kaptanoglu +5 · 3 citations
Chemical Engineering · Engineering · Physics and Astronomy · #Computational Physics (physics.comp-ph) #FOS: Mathematics #FOS: Physical sciences #Fluid Dynamics (physics.flu-dyn) #Fluid Dynamics and Turbulent Flows #Model Reduction and Neural Networks #Numerical Analysis (math.NA) #Rheology and Fluid Dynamics Studies
- Saddle transport and chaos in the double pendulum
2023/01/11 by Kadierdan Kaheman, Jason J. Bramburger, J. Nathan Kutz +1 · 1 voice · 1 citation
Engineering · Physics and Astronomy · #Astro and Planetary Science #Spacecraft Dynamics and Control #Stellar, planetary, and galactic studies
- PySensors 2.0: A Python Package for Sparse Sensor Placement
2021/02/16 by Karnik, Niharika, Bhangale, Yash, de Silva, Brian M. +12 · 3 citations
Engineering · Computer Science · #Sparse and Compressive Sensing Techniques #Gaussian Processes and Bayesian Inference #Machine Learning and Algorithms
- Principal component trajectories for modeling spectrally-continuous dynamics as forced linear systems
2020/05/28 by Daniel Dylewsky, Dylewsky, Daniel, Eurika Kaiser +5 · 1 citation
Engineering · Physics and Astronomy · #Computational Physics (physics.comp-ph) #Energy Load and Power Forecasting #FOS: Electrical engineering #FOS: Physical sciences #Model Reduction and Neural Networks #Power System Optimization and Stability #Systems and Control (eess.SY) #electronic engineering #information engineering
- Deep reinforcement learning for optical systems: A case study of mode-locked lasers
2020/06/10 by Chang Sun, Eurika Kaiser, Sun, Chang +5 · 1 citation
Physics and Astronomy · Computer Science · Engineering · #Advanced Fiber Laser Technologies #Neural Networks and Reservoir Computing #Semiconductor Lasers and Optical Devices
- Data-Driven Modeling for Transonic Aeroelastic Analysis
2023/04/14 by Nicola Fonzi, Fonzi, Nicola, Steven L. Brunton +3 · 1 citation
Engineering · Physics and Astronomy · #Computational Fluid Dynamics and Aerodynamics #FOS: Physical sciences #Fluid Dynamics (physics.flu-dyn) #Fluid Dynamics and Turbulent Flows #Model Reduction and Neural Networks
- Capturing multiscale interactions in fluid flow via Lagrangian coherent structures and modal analysis
2024/10/28 by Morgan R. Jones, Jones, Morgan R., Charles Klewicki +6 · 1 citation
Engineering · #FOS: Physical sciences #Fluid Dynamics (physics.flu-dyn) #Fluid Dynamics and Turbulent Flows #Fluid Dynamics and Vibration Analysis #Vibration and Dynamic Analysis
- Robust, High-Rate Trajectory Tracking on Insect-Scale Soft-Actuated Aerial Robots with Deep-Learned Tube MPC
2022/09/20 by Andrea Tagliabue, Tagliabue, Andrea, Yi‐Hsuan Hsiao +11 · 1 citation
Computer Science · Engineering · #Adaptive Control of Nonlinear Systems #Biomimetic flight and propulsion mechanisms #FOS: Computer and information sciences #Machine Learning (cs.LG) #Robotic Path Planning Algorithms #Robotics (cs.RO)
- Data-Driven Modeling for On-Demand Flow Prescription in Fan-Array Wind Tunnels
2024/12/16 by Alejandro Stefan-Zavala, Stefan-Zavala, Alejandro A., Isabel Scherl +7 · 1 citation
Engineering · Decision Sciences · #Traffic Prediction and Management Techniques #Simulation Techniques and Applications #Vehicle emissions and performance
- An Introduction to Sparse Identification of Nonlinear Dynamics for Engineering Applications
2026/07/16 by Yao Cheng Li, Ana Larrañaga, Steven L. Brunton +1
#cs.LG