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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
Operator Autoencoders: Learning Physical Operations on Encoded Molecular Graphs Willis Hoke D. Shea S. Casey AI4CE 57 0 0 26 May 2021
Estimating the State of Epidemics Spreading with Graph Neural Networks Abhishek Tomy Matteo Razzanelli Francesco Di Lauro Daniela Rus Cosimo Della Santina 76 28 0 10 May 2021
Adaptive Latent Space Tuning for Non-Stationary Distributions A. Scheinker F. Cropp S. Paiagua D. Filippetto OOD 98 3 0 08 May 2021
PCE-PINNs: Physics-Informed Neural Networks for Uncertainty Propagation in Ocean Modeling Björn Lütjens Catherine H. Crawford Mark S. Veillette Dava Newman 96 10 0 05 May 2021
Neural Ordinary Differential Equations for Data-Driven Reduced Order Modeling of Environmental Hydrodynamics S. Dutta Peter Rivera-Casillas Matthew W. Farthing AI4CE 60 13 0 22 Apr 2021
Split Learning Meets Koopman Theory for Wireless Remote Monitoring and Prediction Abanoub M. Girgis Hyowoon Seo Jihong Park M. Bennis Jinho Choi 65 7 0 16 Apr 2021
Weak Form Generalized Hamiltonian Learning Kevin Course Trefor W. Evans P. Nair AI4CE 56 10 0 11 Apr 2021
Learning of Causal Observable Functions for Koopman-DFL Lifting Linearization of Nonlinear Controlled Systems and Its Application to Excavation Automation Nicholas Stearns S. M. I. H. Harry Asada 75 13 0 05 Apr 2021
Deep Learning of Conjugate Mappings J. Bramburger S. Patterson J. Nathan Kutz 75 15 0 01 Apr 2021
Deep KKL: Data-driven Output Prediction for Non-Linear Systems Steeven Janny V. Andrieu Madiha Nadri Wolf Christian Wolf AI4TS 83 13 0 23 Mar 2021
Gaussian processes meet NeuralODEs: A Bayesian framework for learning the dynamics of partially observed systems from scarce and noisy data Mohamed Aziz Bhouri P. Perdikaris 81 21 0 04 Mar 2021
Modern Koopman Theory for Dynamical Systems Steven L. Brunton M. Budišić E. Kaiser J. Nathan Kutz AI4CE 156 423 0 24 Feb 2021
CKNet: A Convolutional Neural Network Based on Koopman Operator for Modeling Latent Dynamics from Pixels Yongqian Xiao Xin Xu Yifei Shi 60 9 0 19 Feb 2021
An Operator Theoretic Approach for Analyzing Sequence Neural Networks Ilana D Naiman Omri Azencot 108 11 0 15 Feb 2021
Meta-Learning for Koopman Spectral Analysis with Short Time-series Tomoharu Iwata Yoshinobu Kawahara AI4TS 57 0 0 09 Feb 2021
Machine learning accelerated computational fluid dynamics Dmitrii Kochkov Jamie A. Smith Ayya Alieva Qing Wang M. Brenner Stephan Hoyer AI4CE 196 884 0 28 Jan 2021
Reproducing kernel Hilbert C*-module and kernel mean embeddings Yuka Hashimoto Isao Ishikawa Masahiro Ikeda Fuyuta Komura Takeshi Katsura Yoshinobu Kawahara 35 11 0 27 Jan 2021
Data-driven discovery of multiscale chemical reactions governed by the law of mass action Juntao Huang Y. Zhou W. Yong 52 6 0 17 Jan 2021
Physics-aware, probabilistic model order reduction with guaranteed stability Sebastian Kaltenbach P. Koutsourelakis DiffM AI4CE 88 15 0 14 Jan 2021
DeepGreen: Deep Learning of Green's Functions for Nonlinear Boundary Value Problems Craig Gin D. Shea Steven L. Brunton J. Nathan Kutz 92 90 0 31 Dec 2020
Gaussian Process Regression constrained by Boundary Value Problems Mamikon A. Gulian A. Frankel L. Swiler 75 25 0 22 Dec 2020
SRoll3: A neural network approach to reduce large-scale systematic effects in the Planck High Frequency Instrument maps Manuel López-Radcenco J. Delouis L. Vibert 15 2 0 17 Dec 2020
Neural Dynamic Mode Decomposition for End-to-End Modeling of Nonlinear Dynamics Tomoharu Iwata Yoshinobu Kawahara 63 12 0 11 Dec 2020
Variational Autoencoders for Learning Nonlinear Dynamics of Physical Systems Ryan Lopez P. Atzberger DRL AI4CE 60 13 0 07 Dec 2020
DeepKoCo: Efficient latent planning with a task-relevant Koopman representation B. V. D. Heijden L. Ferranti Jens Kober Robert Babuška 48 7 0 25 Nov 2020
Forecasting Hamiltonian dynamics without canonical coordinates A. Choudhary J. Lindner Elliott G. Holliday Scott T. Miller S. Sinha W. Ditto 74 26 0 28 Oct 2020
Parameterized Neural Ordinary Differential Equations: Applications to Computational Physics Problems Kookjin Lee E. Parish 71 68 0 28 Oct 2020
Scientific intuition inspired by machine learning generated hypotheses Pascal Friederich Mario Krenn Isaac Tamblyn Alán Aspuru-Guzik AI4CE 93 34 0 27 Oct 2020
Extraction of Discrete Spectra Modes from Video Data Using a Deep Convolutional Koopman Network S. Leask V. McDonell 18 1 0 19 Oct 2020
Deep Learning of Koopman Representation for Control Yiqiang Han Wenjian Hao Umesh Vaidya AI4CE 57 110 0 15 Oct 2020
Stochastic embeddings of dynamical phenomena through variational autoencoders C. A. García P. Félix J. Presedo A. Otero BDL 58 2 0 13 Oct 2020
Derivative-Based Koopman Operators for Real-Time Control of Robotic Systems Giorgos Mamakoukas Maria L. Castaño Xiaobo Tan Todd Murphey 71 92 0 12 Oct 2020
Spacetime Autoencoders Using Local Causal States Adam T. Rupe James P. Crutchfield CML 140 2 0 12 Oct 2020
Modeling Electrical Motor Dynamics using Encoder-Decoder with Recurrent Skip Connection Sagar Verma Nicolas Henwood M. Castella F. Malrait J. Pesquet AI4CE 28 13 0 08 Oct 2020
Transformers for Modeling Physical Systems N. Geneva N. Zabaras AI4CE 119 146 0 04 Oct 2020
A Survey on Machine Learning Applied to Dynamic Physical Systems Sagar Verma AI4CE 16 4 0 21 Sep 2020
Bridging the Gap: Machine Learning to Resolve Improperly Modeled Dynamics Maan Qraitem D. Kularatne Eric Forgoston M. A. Hsieh AI4CE 86 10 0 23 Aug 2020
Hierarchical Deep Learning of Multiscale Differential Equation Time-Steppers Yuying Liu N. Kutz Steven L. Brunton AI4TS 69 78 0 22 Aug 2020
Deep Neural Networks for Nonlinear Model Order Reduction of Unsteady Flows Hamidreza Eivazi H. Veisi M. H. Naderi V. Esfahanian AI4CE 94 173 0 02 Jul 2020
Molecular Latent Space Simulators Hythem Sidky Wei Chen Andrew L. Ferguson AI4CE 83 34 0 01 Jul 2020
Extracting Latent State Representations with Linear Dynamics from Rich Observations Abraham Frandsen Rong Ge 28 2 0 29 Jun 2020
Multiscale Simulations of Complex Systems by Learning their Effective Dynamics Pantelis R. Vlachas G. Arampatzis Caroline Uhler Petros Koumoutsakos AI4CE 107 150 0 24 Jun 2020
Data Driven Control with Learned Dynamics: Model-Based versus Model-Free Approach Wenjian Hao Yiqiang Han 45 6 0 16 Jun 2020
A Survey of Constrained Gaussian Process Regression: Approaches and Implementation Challenges L. Swiler Mamikon A. Gulian A. Frankel Cosmin Safta J. Jakeman GP AI4CE 110 106 0 16 Jun 2020
Reconstruction of turbulent data with deep generative models for semantic inpainting from TURB-Rot database M. Buzzicotti F. Bonaccorso P. C. D. Leoni Luca Biferale AI4CE 68 53 0 16 Jun 2020
Learning Dynamics Models with Stable Invariant Sets Naoya Takeishi Yoshinobu Kawahara 62 18 0 16 Jun 2020
A Tailored Convolutional Neural Network for Nonlinear Manifold Learning of Computational Physics Data using Unstructured Spatial Discretizations John Tencer Kevin Potter AI4CE 61 13 0 11 Jun 2020
Deep Adversarial Koopman Model for Reaction-Diffusion systems K. Balakrishnan Devesh Upadhyay 70 5 0 09 Jun 2020
Deep learning of contagion dynamics on complex networks Charles Murphy Edward Laurence Antoine Allard GNN AI4CE 49 70 0 09 Jun 2020
Memory-Efficient Learning of Stable Linear Dynamical Systems for Prediction and Control Giorgos Mamakoukas Orest Xherija Todd Murphey 60 3 0 06 Jun 2020