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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"

50 / 411 papers shown

Title
Tensorized Transformer for Dynamical Systems Modeling Anna Shalova Ivan Oseledets AI4CE 69 8 0 05 Jun 2020
Optimizing Neural Networks via Koopman Operator Theory Akshunna S. Dogra William T. Redman 78 51 0 03 Jun 2020
Objective-Sensitive Principal Component Analysis for High-Dimensional Inverse Problems M. Elizarev A. Mukhin A. Khlyupin 23 3 0 02 Jun 2020
Data-Driven Continuum Dynamics via Transport-Teleport Duality Jong-Hoon Ahn AI4CE 31 0 0 27 May 2020
Learning Stable Models for Prediction and Control Giorgos Mamakoukas Ian Abraham Todd Murphey 97 39 0 08 May 2020
Physics-informed learning of governing equations from scarce data Zhao Chen Yang Liu Hao Sun PINN AI4CE 117 400 0 05 May 2020
Recurrent neural networks and Koopman-based frameworks for temporal predictions in a low-order model of turbulence Hamidreza Eivazi L. Guastoni P. Schlatter Hossein Azizpour Ricardo Vinuesa AI4CE 60 7 0 01 May 2020
Bayesian differential programming for robust systems identification under uncertainty Yibo Yang Mohamed Aziz Bhouri P. Perdikaris OOD 123 32 0 15 Apr 2020
Multiresolution Convolutional Autoencoders Yuying Liu Colin Ponce Steven L. Brunton J. Nathan Kutz SyDa 52 31 0 10 Apr 2020
From Fourier to Koopman: Spectral Methods for Long-term Time Series Prediction Henning Lange Steven L. Brunton N. Kutz AI4TS 89 80 0 01 Apr 2020
Integrating Scientific Knowledge with Machine Learning for Engineering and Environmental Systems J. Willard X. Jia Shaoming Xu M. Steinbach Vipin Kumar AI4CE 158 415 0 10 Mar 2020
Machine learning based non-Newtonian fluid model with molecular fidelity H. Lei Lei Wu E. Weinan 38 18 0 07 Mar 2020
Forecasting Sequential Data using Consistent Koopman Autoencoders Omri Azencot N. Benjamin Erichson Vanessa Lin Michael W. Mahoney AI4TS AI4CE 206 152 0 04 Mar 2020
Variational inference formulation for a model-free simulation of a dynamical system with unknown parameters by a recurrent neural network K. Yeo D. E. C. Grullon Fan-Keng Sun Duane S. Boning Jayant Kalagnanam BDL 57 3 0 02 Mar 2020
Analysis via Orthonormal Systems in Reproducing Kernel Hilbert $C^*$ -Modules and Applications Yuka Hashimoto Isao Ishikawa Masahiro Ikeda Fuyuta Komura Takeshi Katsura Yoshinobu Kawahara 19 2 0 02 Mar 2020
Dimensionality reduction to maximize prediction generalization capability Takuya Isomura Taro Toyoizumi 47 17 0 01 Mar 2020
Sparsity-promoting algorithms for the discovery of informative Koopman invariant subspaces Shaowu Pan Nicholas Arnold-Medabalimi Karthik Duraisamy 78 48 0 25 Feb 2020
Computer-inspired Quantum Experiments Mario Krenn Manuel Erhard A. Zeilinger 72 75 0 23 Feb 2020
Generalized Kernel-Based Dynamic Mode Decomposition P. Héas Cédric Herzet B. Combès 20 6 0 11 Feb 2020
Hamiltonian neural networks for solving equations of motion M. Mattheakis David Sondak Akshunna S. Dogra P. Protopapas 108 59 0 29 Jan 2020
Interpretable Conservation Law Estimation by Deriving the Symmetries of Dynamics from Trained Deep Neural Networks Yoh-ichi Mototake PINN AI4CE 62 14 0 31 Dec 2019
Pontryagin Differentiable Programming: An End-to-End Learning and Control Framework Wanxin Jin Zhaoran Wang Zhuoran Yang Shaoshuai Mou 96 80 0 30 Dec 2019
Tensor Basis Gaussian Process Models of Hyperelastic Materials A. Frankel Reese E. Jones L. Swiler 81 43 0 23 Dec 2019
Interpretable Embeddings From Molecular Simulations Using Gaussian Mixture Variational Autoencoders Yasemin Bozkurt Varolgunes T. Bereau J. F. Rudzinski DRL 58 44 0 22 Dec 2019
Deep learning to discover and predict dynamics on an inertial manifold Alec J. Linot M. Graham AI4CE 78 75 0 20 Dec 2019
Parameter-Conditioned Sequential Generative Modeling of Fluid Flows Jeremy Morton F. Witherden Mykel J. Kochenderfer GAN MedIm AI4CE 61 10 0 14 Dec 2019
Density Propagation with Characteristics-based Deep Learning Tenavi Nakamura-Zimmerer D. Venturi Q. Gong W. Kang AI4CE 49 1 0 21 Nov 2019
Deep Learning Models for Global Coordinate Transformations that Linearize PDEs Craig Gin Bethany Lusch Steven L. Brunton J. Nathan Kutz 83 41 0 07 Nov 2019
Learning Compositional Koopman Operators for Model-Based Control Yunzhu Li Hao He Jiajun Wu Dina Katabi Antonio Torralba 114 121 0 18 Oct 2019
Backpropagation Algorithms and Reservoir Computing in Recurrent Neural Networks for the Forecasting of Complex Spatiotemporal Dynamics Pantelis R. Vlachas Jaideep Pathak Brian R. Hunt T. Sapsis M. Girvan Edward Ott Petros Koumoutsakos AI4TS 94 400 0 09 Oct 2019
Neural Canonical Transformation with Symplectic Flows Shuo-Hui Li Chen Dong Linfeng Zhang Lei Wang DRL 119 28 0 30 Sep 2019
Towards Scalable Koopman Operator Learning: Convergence Rates and A Distributed Learning Algorithm Zhiyuan Liu Guohui Ding Lijun Chen Enoch Yeung 25 3 0 30 Sep 2019
Data-driven approximation of the Koopman generator: Model reduction, system identification, and control Stefan Klus Feliks Nuske Sebastian Peitz Jan-Hendrik Niemann C. Clementi Christof Schütte 118 230 0 23 Sep 2019
Tensor-based computation of metastable and coherent sets Feliks Nuske Patrick Gelß Stefan Klus C. Clementi 32 13 0 12 Aug 2019
Predicting Critical Transitions in Multiscale Dynamical Systems Using Reservoir Computing Soon Hoe Lim L. T. Giorgini W. Moon J. Wettlaufer 64 4 0 10 Aug 2019
A unified sparse optimization framework to learn parsimonious physics-informed models from data Kathleen P. Champion P. Zheng Aleksandr Aravkin Steven L. Brunton J. Nathan Kutz AI4CE 76 119 0 25 Jun 2019
Active Learning of Dynamics for Data-Driven Control Using Koopman Operators Ian Abraham Todd Murphey 71 166 0 12 Jun 2019
Physics-Informed Probabilistic Learning of Linear Embeddings of Non-linear Dynamics With Guaranteed Stability Shaowu Pan Karthik Duraisamy 140 138 0 09 Jun 2019
A Novel Modeling Approach for All-Dielectric Metasurfaces Using Deep Neural Networks S. An Clayton Fowler B. Zheng M. Shalaginov H. Tang ... C. Rivero‐Baleine K. Richardson T. Gu Juejun Hu Hualiang Zhang 42 17 0 08 Jun 2019
Machine Learning for Fluid Mechanics Steven Brunton B. R. Noack Petros Koumoutsakos AI4CE PINN 103 2,146 0 27 May 2019
Physics-informed Autoencoders for Lyapunov-stable Fluid Flow Prediction N. Benjamin Erichson Michael Muehlebach Michael W. Mahoney AI4CE PINN 75 141 0 26 May 2019
Explainable Machine Learning for Scientific Insights and Discoveries R. Roscher B. Bohn Marco F. Duarte Jochen Garcke XAI 120 677 0 21 May 2019
Time-varying Autoregression with Low Rank Tensors K. Harris Aleksandr Aravkin Rajesh P. N. Rao Bingni W. Brunton AI4TS 80 20 0 21 May 2019
Exploring helical dynamos with machine learning F. Nauman J. Nättilä AI4CE 13 4 0 20 May 2019
Enforcing Statistical Constraints in Generative Adversarial Networks for Modeling Chaotic Dynamical Systems Jin-Long Wu K. Kashinath A. Albert D. Chirila P. Prabhat Heng Xiao AI4CE 66 134 0 13 May 2019
Physically-interpretable classification of biological network dynamics for complex collective motions Keisuke Fujii Naoya Takeishi Motokazu Hojo Yuki Inaba Yoshinobu Kawahara 110 11 0 13 May 2019
Short note on the behavior of recurrent neural network for noisy dynamical system K. Yeo 42 13 0 05 Apr 2019
Time Series Source Separation using Dynamic Mode Decomposition Arvind Prasadan R. Nadakuditi AI4TS 88 6 0 04 Mar 2019
Video Extrapolation with an Invertible Linear Embedding Robert Pottorff Jared Nielsen David Wingate 53 5 0 01 Mar 2019
Deep Variational Koopman Models: Inferring Koopman Observations for Uncertainty-Aware Dynamics Modeling and Control Jeremy Morton F. Witherden Mykel J Kochenderfer 85 47 0 26 Feb 2019