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Deep learning for universal linear embeddings of nonlinear dynamics

27 December 2017

Bethany Lusch

J. Nathan Kutz

Steven L. Brunton

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Papers citing "Deep learning for universal linear embeddings of nonlinear dynamics"

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Title
Learned Coarse Models for Efficient Turbulence Simulation Kimberly L. Stachenfeld D. Fielding Dmitrii Kochkov M. Cranmer Tobias Pfaff Jonathan Godwin Can Cui S. Ho Peter W. Battaglia Alvaro Sanchez-Gonzalez AI4CE 121 84 0 31 Dec 2021
Deep Learning for Stability Analysis of a Freely Vibrating Sphere at Moderate Reynolds Number A. Chizfahm R. Jaiman AI4CE 29 0 0 18 Dec 2021
Manifold embedding data-driven mechanics B. Bahmani WaiChing Sun PINN AI4CE 76 9 0 18 Dec 2021
Data-driven modelling of nonlinear dynamics by barycentric coordinates and memory Niklas Wulkow P. Koltai V. Sunkara Christof Schütte 75 3 0 13 Dec 2021
Output-weighted and relative entropy loss functions for deep learning precursors of extreme events S. Rudy T. Sapsis 73 16 0 01 Dec 2021
Rigorous data-driven computation of spectral properties of Koopman operators for dynamical systems Matthew J. Colbrook Alex Townsend 95 72 0 29 Nov 2021
Learning Physical Concepts in Cyber-Physical Systems: A Case Study Henrik S. Steude Alexander Windmann Oliver Niggemann AI4CE 72 1 0 28 Nov 2021
Learning Low-Dimensional Quadratic-Embeddings of High-Fidelity Nonlinear Dynamics using Deep Learning P. Goyal P. Benner AI4CE 57 5 0 25 Nov 2021
Physics-enhanced Neural Networks in the Small Data Regime Jonas Eichelsdörfer Sebastian Kaltenbach P. Koutsourelakis AI4CE PINN 45 5 0 19 Nov 2021
Neural optimal feedback control with local learning rules Johannes Friedrich Siavash Golkar Shiva Farashahi A. Genkin Anirvan M. Sengupta D. Chklovskii 39 13 0 12 Nov 2021
Solving PDE-constrained Control Problems Using Operator Learning Rakhoon Hwang Jae Yong Lee J. Shin H. Hwang AI4CE 170 48 0 09 Nov 2021
Statistical properties of large data sets with linear latent features P. Fleig I. Nemenman 65 5 0 08 Nov 2021
Generative Adversarial Network for Probabilistic Forecast of Random Dynamical System K. Yeo Zan Li Wesley M. Gifford SyDa GAN AI4TS AI4CE 108 4 0 04 Nov 2021
Symmetry-Aware Autoencoders: s-PCA and s-nlPCA Simon Kneer T. Sayadi D. Sipp Peter J. Schmid Georgios Rigas 50 10 0 04 Nov 2021
Deeptime: a Python library for machine learning dynamical models from time series data Moritz Hoffmann Martin K. Scherer Tim Hempel Andreas Mardt Brian M. de Silva ... Stefan Klus Hao Wu N. Kutz Steven L. Brunton Frank Noé AI4CE 101 107 0 28 Oct 2021
A Neural Network Ensemble Approach to System Identification Elisa Negrini G. Citti L. Capogna 51 2 0 15 Oct 2021
Learning Stable Koopman Embeddings Fletcher Fan Yeman Fan D. Rye Guodong Shi I. Manchester 92 34 0 13 Oct 2021
Chaos as an interpretable benchmark for forecasting and data-driven modelling W. Gilpin AI4TS 75 82 0 11 Oct 2021
Deep Identification of Nonlinear Systems in Koopman Form Lucian-Cristian Iacob G. Beintema Maarten Schoukens R. Tóth 52 16 0 06 Oct 2021
Enhancing Computational Fluid Dynamics with Machine Learning Ricardo Vinuesa Steven L. Brunton AI4CE 188 385 0 05 Oct 2021
Applying Machine Learning to Study Fluid Mechanics Steven L. Brunton PINN AI4CE 63 100 0 05 Oct 2021
Data-driven Nonlinear Model Reduction to Spectral Submanifolds in Mechanical Systems Mattia Cenedese Joar Axås Haocheng Yang M. Eriten George Haller 154 41 0 05 Oct 2021
Exploration of Artificial Intelligence-oriented Power System Dynamic Simulators Tannan Xiao Ying-Cong Chen Jianquan Wang Shaowei Huang Weilin Tong Tirui He 51 15 0 03 Oct 2021
Self-Supervised Decomposition, Disentanglement and Prediction of Video Sequences while Interpreting Dynamics: A Koopman Perspective Armand Comas Massague S. Ghimire Haolin Li Octavia Camps Mario Sznaier 112 2 0 01 Oct 2021
Extended dynamic mode decomposition with dictionary learning using neural ordinary differential equations H. Terao Sho Shirasaka Hideyuki Suzuki 58 6 0 01 Oct 2021
Learning Transport Processes with Machine Intelligence F. Miniati G. Gregori AI4CE 60 4 0 27 Sep 2021
Model reduction for the material point method via an implicit neural representation of the deformation map Julius Berner Maurizio M. Chiaramonte E. Grinspun Kevin Carlberg 104 15 0 25 Sep 2021
Learning Dynamics from Noisy Measurements using Deep Learning with a Runge-Kutta Constraint P. Goyal P. Benner 81 9 0 23 Sep 2021
Analysis of chaotic dynamical systems with autoencoders N. Almazova G. D. Barmparis G. P. Tsironis 23 7 0 22 Sep 2021
Recurrent Neural Networks for Partially Observed Dynamical Systems Uttam Bhat S. Munch PINN AI4CE 65 9 0 21 Sep 2021
Stochastic Adversarial Koopman Model for Dynamical Systems K. Balakrishnan Devesh Upadhyay 45 8 0 10 Sep 2021
Supervised DKRC with Images for Offline System Identification Alexander Krolicki P. Lavertu 52 1 0 06 Sep 2021
Towards high-accuracy deep learning inference of compressible turbulent flows over aerofoils Li-Wei Chen Nils Thuerey AI4CE 67 9 0 05 Sep 2021
Towards extraction of orthogonal and parsimonious non-linear modes from turbulent flows Hamidreza Eivazi S. L. C. Martínez S. Hoyas Ricardo Vinuesa 93 96 0 03 Sep 2021
Physics-informed Neural Network for Nonlinear Dynamics in Fiber Optics Xiaotian Jiang Danshi Wang Qirui Fan Min Zhang Chao Lu A. Lau AI4CE PINN 39 85 0 01 Sep 2021
Data-Driven Reduced-Order Modeling of Spatiotemporal Chaos with Neural Ordinary Differential Equations Alec J. Linot M. Graham 52 51 0 31 Aug 2021
Data-driven discovery of intrinsic dynamics D. Floryan M. Graham AI4CE 183 78 0 12 Aug 2021
Deep Learning Enhanced Dynamic Mode Decomposition D. J. Alford-Lago C. Curtis Alexander T. Ihler Opal Issan 75 36 0 10 Aug 2021
Generalizing Dynamic Mode Decomposition: Balancing Accuracy and Expressiveness in Koopman Approximations Masih Haseli Jorge Cortes 61 15 0 08 Aug 2021
Bayesian Deep Learning for Partial Differential Equation Parameter Discovery with Sparse and Noisy Data Christophe Bonneville Christopher Earls 96 14 0 05 Aug 2021
Reconstructing a dynamical system and forecasting time series by self-consistent deep learning Zhe Wang C. Guet AI4TS 26 4 0 04 Aug 2021
A purely data-driven framework for prediction, optimization, and control of networked processes: application to networked SIS epidemic model A. Tavasoli T. Henry Heman Shakeri 81 4 0 01 Aug 2021
Discovering Sparse Interpretable Dynamics from Partial Observations Peter Y. Lu Joan Ariño Bernad Marin Soljacic AI4CE 83 25 0 22 Jul 2021
Data-driven reduced order modeling of environmental hydrodynamics using deep autoencoders and neural ODEs S. Dutta Peter Rivera-Casillas Orie M. Cecil Matthew W. Farthing E. Perracchione M. Putti AI4CE 56 7 0 06 Jul 2021
Physics-Guided Deep Learning for Dynamical Systems: A Survey Rui Wang Rose Yu AI4CE PINN 117 69 0 02 Jul 2021
Active Learning in Robotics: A Review of Control Principles Annalisa T. Taylor Thomas A. Berrueta Todd Murphey 98 77 0 25 Jun 2021
Physics perception in sloshing scenes with guaranteed thermodynamic consistency B. Moya Alberto Badías D. González Francisco Chinesta Elías Cueto 76 14 0 24 Jun 2021
Deep Probabilistic Koopman: Long-term time-series forecasting under periodic uncertainties Alex Troy Mallen Henning Lange J. Nathan Kutz AI4TS 63 8 0 10 Jun 2021
Encoding physics to learn reaction-diffusion processes Chengping Rao Pu Ren Qi Wang O. Buyukozturk Haoqin Sun Yang Liu PINN AI4CE DiffM 107 97 0 09 Jun 2021
Calibrating multi-dimensional complex ODE from noisy data via deep neural networks Kexuan Li Fangfang Wang Ruiqi Liu Fan Yang Zuofeng Shang 61 7 0 07 Jun 2021