Data-driven discovery of coordinates and governing equations

Reactive SINDy: Discovering governing reactions from concentration data

(2019) Moritz Hoffmann et al.   JOURNAL OF CHEMICAL PHYSICS

Learning data-driven discretizations for partial differential equations

(2019) Yohai Bar-Sinai et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Deep learning of dynamics and signal-noise decomposition with time-stepping constraints

(2019) Samuel H. Rudy et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Recovering missing CFD data for high-order discretizations using deep neural networks and dynamics learning

(2019) Kevin T. Carlberg et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Model reduction of dynamical systems on nonlinear manifolds using deep convolutional autoencoders

(2019) Kookjin Lee et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Time-lagged autoencoders: Deep learning of slow collective variables for molecular kinetics

(2018) Christoph Wehmeyer et al.   JOURNAL OF CHEMICAL PHYSICS

Constrained sparse Galerkin regression

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

Model-Free Prediction of Large Spatiotemporally Chaotic Systems from Data: A Reservoir Computing Approach

(2018) Jaideep Pathak et al.   PHYSICAL REVIEW LETTERS

Data-driven forecasting of high-dimensional chaotic systems with long short-term memory networks

(2018) Pantelis R. Vlachas et al.   PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES

VAMPnets for deep learning of molecular kinetics

(2018) Andreas Mardt et al.   Nature Communications

Turbulence Modeling in the Age of Data

(2018) Karthik Duraisamy et al.   Annual Review 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

Deep learning for universal linear embeddings of nonlinear dynamics

(2018) Bethany Lusch et al.   Nature Communications

Sparse structural system identification method for nonlinear dynamic systems with hysteresis/inelastic behavior

(2018) Zhilu Lai et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Exact Recovery of Chaotic Systems from Highly Corrupted Data

(2017) Giang Tran et al.   MULTISCALE MODELING & SIMULATION

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

Model selection for dynamical systems via sparse regression and information criteria

(2017) N. M. Mangan et al.   PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES

Learning partial differential equations via data discovery and sparse optimization

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

Chaos as an intermittently forced linear system

(2017) Steven L. Brunton et al.   Nature Communications

Data-driven discovery of partial differential equations

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

Data-driven operator inference for nonintrusive projection-based model reduction

(2016) Benjamin Peherstorfer et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

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

A Data–Driven Approximation of the Koopman Operator: Extending Dynamic Mode Decomposition

(2015) Matthew O. Williams et al.   JOURNAL OF NONLINEAR SCIENCE

A Survey of Projection-Based Model Reduction Methods for Parametric Dynamical Systems

(2015) Peter Benner et al.   SIAM REVIEW

Sparse dynamics for partial differential equations

(2013) H. Schaeffer et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Dynamic mode decomposition of numerical and experimental data

(2010) PETER J. SCHMID   JOURNAL OF FLUID MECHANICS

Double Sparsity: Learning Sparse Dictionaries for Sparse Signal Approximation

(2009) R. Rubinstein et al.   IEEE TRANSACTIONS ON SIGNAL PROCESSING

Spectral analysis of nonlinear flows

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

Distilling Free-Form Natural Laws from Experimental Data

(2009) Michael Schmidt et al.   SCIENCE