Ensemble-SINDy: Robust sparse model discovery in the low-data, high-noise limit, with active learning and control

Sparsifying priors for Bayesian uncertainty quantification in model discovery

(2022) Seth M. Hirsh et al.   Royal Society Open Science

Galerkin force model for transient and post-transient dynamics of the fluidic pinball

(2021) Nan Deng et al.   JOURNAL OF FLUID MECHANICS

Sparse identification of multiphase turbulence closures for coupled fluid–particle flows – CORRIGENDUM

(2021) S. Beetham et al.   JOURNAL OF FLUID MECHANICS

Supervised learning from noisy observations: Combining machine-learning techniques with data assimilation

(2021) Georg A. Gottwald et al.   PHYSICA D-NONLINEAR PHENOMENA

Nonlinear stochastic modelling with Langevin regression

(2021) J. L. Callaham et al.   PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES

Robust learning from noisy, incomplete, high-dimensional experimental data via physically constrained symbolic regression

(2021) Patrick A. K. Reinbold et al.   Nature Communications

Sparse nonlinear models of chaotic electroconvection

(2021) Yifei Guan et al.   Royal Society Open Science

Promoting global stability in data-driven models of quadratic nonlinear dynamics

(2021) Alan A. Kaptanoglu et al.   Physical Review Fluids

Combining machine learning and data assimilation to forecast dynamical systems from noisy partial observations

(2021) Georg A. Gottwald et al.   CHAOS

Weak SINDy for partial differential equations

(2021) Daniel A. Messenger et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Data‐driven Equation Discovery of Ocean Mesoscale Closures

(2020) Laure Zanna et al.   GEOPHYSICAL RESEARCH LETTERS

Data-driven modeling of the chaotic thermal convection in an annular thermosyphon

(2020) Jean-Christophe Loiseau   THEORETICAL AND COMPUTATIONAL FLUID DYNAMICS

Learning Equations from Biological Data with Limited Time Samples

(2020) John T. Nardini et al.   BULLETIN OF MATHEMATICAL BIOLOGY

Bayesian system ID: optimal management of parameter, model, and measurement uncertainty

(2020) Nicholas Galioto et al.   NONLINEAR DYNAMICS

SINDy-PI: a robust algorithm for parallel implicit sparse identification of nonlinear dynamics

(2020) Kadierdan Kaheman et al.   PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES

Formulating turbulence closures using sparse regression with embedded form invariance

(2020) S. Beetham et al.   Physical Review Fluids

Sparse identification of truncation errors

(2019) Stephan Thaler et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Robust and optimal sparse regression for nonlinear PDE models

(2019) Daniel R. Gurevich et al.   CHAOS

Data-driven discovery of coordinates and governing equations

(2019) Kathleen Champion et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Discovery of Algebraic Reynolds-Stress Models Using Sparse Symbolic Regression

(2019) Martin Schmelzer et al.   FLOW TURBULENCE AND COMBUSTION

Sparse learning of stochastic dynamical equations

(2018) Lorenzo Boninsegna et al.   JOURNAL OF CHEMICAL PHYSICS

Sparse reduced-order modelling: sensor-based dynamics to full-state estimation

(2018) Jean-Christophe Loiseau et al.   JOURNAL OF FLUID MECHANICS

Constrained sparse Galerkin regression

(2018) Jean-Christophe Loiseau et al.   JOURNAL OF FLUID MECHANICS

Spectral proper orthogonal decomposition and its relationship to dynamic mode decomposition and resolvent analysis

(2018) Aaron Towne et al.   JOURNAL OF FLUID MECHANICS

Sparse identification of nonlinear dynamics for model predictive control in the low-data limit

(2018) E. Kaiser et al.   PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES

Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

(2018) M. Raissi et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Machine learning of linear differential equations using Gaussian processes

(2017) Maziar Raissi et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Sparse identification of a predator-prey system from simulation data of a convection model

(2017) Magnus Dam et al.   PHYSICS OF PLASMAS

Reconstruction of normal forms by learning informed observation geometries from data

(2017) Or Yair et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Learning partial differential equations via data discovery and sparse optimization

(2017) Hayden Schaeffer   PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES

Data-driven discovery of partial differential equations

(2017) Samuel H. Rudy et al.   Science Advances

Sparse identification for nonlinear optical communication systems: SINO method

(2016) Mariia Sorokina et al.   OPTICS EXPRESS

Discovering governing equations from data by sparse identification of nonlinear dynamical systems

(2016) Steven L. Brunton et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Automated adaptive inference of phenomenological dynamical models

(2015) Bryan C. Daniels et al.   Nature Communications

Efficient Inference of Parsimonious Phenomenological Models of Cellular Dynamics Using S-Systems and Alternating Regression

(2015) Bryan C. Daniels et al.   PLoS One

Model predictive control: Recent developments and future promise

(2014) David Q. Mayne   AUTOMATICA

Analysis of Fluid Flows via Spectral Properties of the Koopman Operator

(2012) Igor Mezić   Annual Review of Fluid Mechanics

Nonlinear Laplacian spectral analysis for time series with intermittency and low-frequency variability

(2012) D. Giannakis et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Active Learning From Stream Data Using Optimal Weight Classifier Ensemble

(2010) Xingquan Zhu et al.   IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS

Dynamic mode decomposition of numerical and experimental data

(2010) PETER J. SCHMID   JOURNAL OF FLUID MECHANICS

Stability selection

(2010) Nicolai Meinshausen et al.   JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY

Spectral analysis of nonlinear flows

(2009) CLARENCE W. ROWLEY et al.   JOURNAL OF FLUID MECHANICS

Normal forms for reduced stochastic climate models

(2009) A. J. Majda et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Distilling Free-Form Natural Laws from Experimental Data

(2009) Michael Schmidt et al.   SCIENCE

Nonlinear system modeling and predictive control using the RBF nets-based quasi-linear ARX model

(2008) Hui Peng et al.   CONTROL ENGINEERING PRACTICE