vix.ing · top · new · best · stats · spec

J. Nathan Kutz

  1. 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
  2. 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
  3. 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
  4. 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
  5. 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
  6. Stabilized pulse spacing in soliton lasers due to gain depletion and recovery
    1998/01/01 by J.N. Kutz, J. Nathan Kutz, B.C. Collings +5 · 12 citations
    Physics and Astronomy · Engineering · #Advanced Fiber Laser Technologies #Laser-Matter Interactions and Applications #Optical Network Technologies
  7. Extracting spatial–temporal coherent patterns in large-scale neural recordings using dynamic mode decomposition
    2016/01/01 by Bingni W. Brunton, Lise A. Johnson, Jeffrey G. Ojemann +1 · 8 citations
  8. A Unified Framework for Sparse Relaxed Regularized Regression: SR3
    2018/07/14 by Peng Zheng, Travis Askham, Zheng, Peng +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
  9. Multi-Resolution Dynamic Mode Decomposition
    2015/06/01 by J. Nathan Kutz, Kutz, J. Nathan, Xing Fu +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
  10. 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
  11. SINDy with Control: A Tutorial
    2021/08/30 by Urban Fasel, Eurika Kaiser, Fasel, Urban +7 · 8 citations
    Physics and Astronomy · Engineering · #Model Reduction and Neural Networks #Control Systems and Identification #Fault Detection and Control Systems
  12. Variable projection methods for an optimized dynamic mode decomposition
    2017/04/01 by Travis Askham, Askham, Travis, J. Nathan Kutz +1 · 7 citations
    Decision Sciences · Engineering · #37M02 #49M02 #65P02 #Control Systems and Identification #FOS: Mathematics #Fault Detection and Control Systems #Numerical Analysis (math.NA) #Scientific Measurement and Uncertainty Evaluation
  13. 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)
  14. Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributions from Data
    2020/09/12 by Kadierdan Kaheman, Kaheman, Kadierdan, Steven L. Brunton +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
  15. Mode‐Locked Soliton Lasers
    2006/01/01 by J. Nathan Kutz · 4 citations
    Physics and Astronomy · #Advanced Fiber Laser Technologies #Nonlinear Photonic Systems #Laser-Matter Interactions and Applications
  16. Data-Driven Aerospace Engineering: Reframing the Industry with Machine\n Learning
    2020/08/24 by Steven L. Brunton, Brunton, Steven L., J. Nathan Kutz +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
  17. 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
  18. 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
  19. Sparsifying Priors for Bayesian Uncertainty Quantification in Model Discovery
    2021/07/05 by Seth M. Hirsh, Hirsh, Seth M., David A. Barajas‐Solano +3 · 5 citations
    Physics and Astronomy · Computer Science · Engineering · #Model Reduction and Neural Networks #Gaussian Processes and Bayesian Inference #Control Systems and Identification
  20. 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
  21. 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
  22. 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)
  23. Discrepancy Modeling Framework: Learning missing physics, modeling systematic residuals, and disambiguating between deterministic and random effects
    2022/03/10 by Megan R. Ebers, Katherine M. Steele, Ebers, Megan R. +3 · 4 citations
    Engineering · Physics and Astronomy · Decision Sciences · #Fault Detection and Control Systems #Model Reduction and Neural Networks #Scientific Measurement and Uncertainty Evaluation
  24. Learning Discrepancy Models From Experimental Data
    2019/09/18 by Kadierdan Kaheman, Kaheman, Kadierdan, Eurika Kaiser +7 · 3 citations
    Physics and Astronomy · Engineering · #Model Reduction and Neural Networks #Hydraulic and Pneumatic Systems #Fault Detection and Control Systems
  25. 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
  26. 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
  27. Convergence of uncertainty estimates in Ensemble and Bayesian sparse model discovery
    2023/01/30 by Liyao Gao, Urban Fasel, Gao, L. Mars +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
  28. A toolkit for data-driven discovery of governing equations in high-noise regimes
    2021/11/08 by Charles B. Delahunt, Delahunt, Charles B., J. Nathan Kutz +1 · 3 citations
    Biochemistry, Genetics and Molecular Biology · Computer Science · #68T05 #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #I.2.6 #J.2 #Machine Learning (cs.LG) #Metabolomics and Mass Spectrometry Studies #Neural Networks and Applications
  29. Leveraging arbitrary mobile sensor trajectories with shallow recurrent decoder networks for full-state reconstruction
    2023/07/20 by Megan R. Ebers, Jan P. Williams, Ebers, Megan R. +5 · 4 citations
    Computer Science · #Target Tracking and Data Fusion in Sensor Networks #Time Series Analysis and Forecasting #Gaussian Processes and Bayesian Inference
  30. Reduced order modeling with shallow recurrent decoder networks
    2025/02/15 by Matteo Tomasetto, Tomasetto, Matteo, Jan P. Williams +7 · 9 citations
    Physics and Astronomy · Computer Science · #Model Reduction and Neural Networks #Neural Networks and Reservoir Computing #Generative Adversarial Networks and Image Synthesis
  31. 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
  32. Data-driven discovery of governing equations for coarse-grained heterogeneous network dynamics
    2022/05/23 by Katherine Owens, J. Nathan Kutz, Owens, Katherine +1 · 2 citations
    Computer Science · Engineering · #34 #37 #Dynamical Systems (math.DS) #FOS: Mathematics #Nonlinear Dynamics and Pattern Formation #Slime Mold and Myxomycetes Research
  33. 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
  34. 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
  35. Robust State Estimation from Partial Out-Core Measurements with Shallow Recurrent Decoder for Nuclear Reactors
    2024/09/19 by Stefano Riva, Carolina Introini, Riva, Stefano +5 · 4 citations
    Engineering · #Computational Physics (physics.comp-ph) #FOS: Mathematics #FOS: Physical sciences #Fault Detection and Control Systems #Instrumentation and Detectors (physics.ins-det) #Nuclear Engineering Thermal-Hydraulics #Nuclear reactor physics and engineering #Numerical Analysis (math.NA)
  36. 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
  37. 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
  38. 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
  39. Principal component trajectories for modeling spectrally-continuous dynamics as forced linear systems
    2020/05/28 by Daniel Dylewsky, Eurika Kaiser, Dylewsky, Daniel +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
  40. 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
  41. Statistical Mechanics of Dynamical System Identification
    2024/03/04 by Andrei A. Klishin, Joseph Bakarji, Klishin, Andrei A. +5 · 2 citations
    Engineering · Computer Science · #Control Systems and Identification #Neural Networks and Applications #Fault Detection and Control Systems
  42. Data-driven sensor placement with shallow decoder networks
    2022/02/10 by Jan M. Williams, Williams, Jan, Olivia Zahn +3 · 1 citation
    Computer Science · Engineering · Physics and Astronomy · #Dynamical Systems (math.DS) #FOS: Mathematics #Model Reduction and Neural Networks #Sparse and Compressive Sensing Techniques #Target Tracking and Data Fusion in Sensor Networks
  43. Saddle Transport and Chaos in the Double Pendulum
    2022/09/21 by Kadierdan Kaheman, Jason J. Bramburger, Kaheman, Kadierdan +5 · 1 citation
    Engineering · Physics and Astronomy · #37J46 #65P99 #Astro and Planetary Science #Dynamical Systems (math.DS) #FOS: Mathematics #Solar and Space Plasma Dynamics #Spacecraft Dynamics and Control
  44. Shallow Recurrent Decoder for Reduced Order Modeling of Plasma Dynamics
    2024/05/20 by J. Nathan Kutz, Kutz, J. Nathan, Maryam Reza +5 · 1 citation
    Engineering · Mathematics · #Computational Physics (physics.comp-ph) #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG) #Numerical methods for differential equations #Particle accelerators and beam dynamics #Pattern Formation and Solitons (nlin.PS) #Plasma Diagnostics and Applications #Plasma Physics (physics.plasm-ph)
  45. Bayesian autoencoders for data-driven discovery of coordinates, governing equations and fundamental constants
    2022/11/19 by Liyao Gao, Gao, L. Mars, J. Nathan Kutz +1 · 1 citation
    Computer Science · Physics and Astronomy · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Gamma-ray bursts and supernovae #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks
  46. Reservoir computing for system identification and predictive control with limited data
    2024/10/23 by J. Nathan Kutz, Williams, Jan P., Kutz, J. Nathan +2 · 1 citation
    Engineering · Computer Science · #Reservoir Engineering and Simulation Methods #Neural Networks and Applications #Advanced Control Systems Optimization
  47. Robust, High-Rate Trajectory Tracking on Insect-Scale Soft-Actuated Aerial Robots with Deep-Learned Tube MPC
    2022/09/20 by Andrea Tagliabue, Yi‐Hsuan Hsiao, Tagliabue, Andrea +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)
  48. Data-Induced Interactions of Sparse Sensors Using Statistical Physics
    2023/07/21 by Andrei A. Klishin, Klishin, Andrei A., J. Nathan Kutz +3 · 2 citations
    Physics and Astronomy · #Advanced Thermodynamics and Statistical Mechanics #Computational Physics (physics.comp-ph) #FOS: Computer and information sciences #FOS: Electrical engineering #FOS: Mathematics #FOS: Physical sciences #Machine Learning (cs.LG) #Optimization and Control (math.OC) #Signal Processing (eess.SP) #Statistical Mechanics (cond-mat.stat-mech) #Statistical Mechanics and Entropy #Theoretical and Computational Physics #electronic engineering #information engineering
  49. Real-time optimal control with shallow recurrent decoder networks
    2026/07/21 by Matteo Tomasetto, Francesco Braghin, J. Nathan Kutz +1
    #cs.LG #math.OC
  50. Origins and mitigation of double descent in reduced order modeling
    2026/07/29 by Andrei A. Klishin, J. Nathan Kutz, Krithika Manohar
    Computer Science · Mathematics · Physics and Astronomy · #cs.LG #math.DS #physics.data-an #stat.ML