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Learning Koopman Invariant Subspaces for Dynamic Mode Decomposition

12 October 2017

Papers citing "Learning Koopman Invariant Subspaces for Dynamic Mode Decomposition"

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Title
Challenges and opportunities for machine learning in multiscale computational modeling Phong C. H. Nguyen Joseph B. Choi H. Udaykumar Stephen Seung-Yeob Baek AI4CE 56 10 0 22 Mar 2023
Machine learning with data assimilation and uncertainty quantification for dynamical systems: a review Sibo Cheng César Quilodrán-Casas Said Ouala A. Farchi Che Liu ... Weiping Ding Yike Guo A. Carrassi Marc Bocquet Rossella Arcucci AI4CE 81 138 0 18 Mar 2023
Leveraging Neural Koopman Operators to Learn Continuous Representations of Dynamical Systems from Scarce Data Anthony Frion Lucas Drumetz M. Dalla Mura Guillaume Tochon Abdeldjalil Aissa El Bey AI4TS AI4CE 62 5 0 13 Mar 2023
Koopman neural operator as a mesh-free solver of non-linear partial differential equations Wei Xiong Xiaomeng Huang Ziyang Zhang Ruixuan Deng Pei Sun Yang Tian AI4CE 87 35 0 24 Jan 2023
KoopmanLab: machine learning for solving complex physics equations Wei Xiong Muyuan Ma Xiaomeng Huang Ziyang Zhang Pei Sun Yang Tian AI4CE 73 15 0 03 Jan 2023
Modeling Nonlinear Dynamics in Continuous Time with Inductive Biases on Decay Rates and/or Frequencies Tomoharu Iwata Yoshinobu Kawahara AI4TS AI4CE 104 0 0 26 Dec 2022
Eigenvalue initialisation and regularisation for Koopman autoencoders Jack W. Miller Charles OÑeill N. Constantinou Omri Azencot 64 2 0 23 Dec 2022
Learning Invariant Subspaces of Koopman Operators--Part 2: Heterogeneous Dictionary Mixing to Approximate Subspace Invariance Charles A. Johnson Shara Balakrishnan Enoch Yeung 39 1 0 14 Dec 2022
Learning Invariant Subspaces of Koopman Operators--Part 1: A Methodology for Demonstrating a Dictionary's Approximate Subspace Invariance Charles A. Johnson Shara Balakrishnan Enoch Yeung 27 1 0 14 Dec 2022
Credit Assignment for Trained Neural Networks Based on Koopman Operator Theory Zhen Liang Changyuan Zhao Wanwei Liu Bai Xue Wenjing Yang Zhengbin Pang 64 1 0 02 Dec 2022
Physics-Informed Koopman Network Yuying Liu A. Sholokhov Hassan Mansour S. Nabi AI4CE 92 3 0 17 Nov 2022
DLKoopman: A deep learning software package for Koopman theory Sourya Dey Eric K. Davis AI4CE 74 4 0 15 Nov 2022
Generalized Quadratic Embeddings for Nonlinear Dynamics using Deep Learning P. Goyal P. Benner 74 12 0 01 Nov 2022
Deep Koopman with Control: Spectral Analysis of Soft Robot Dynamics N. Komeno B. Michael Katharina Küchler Edgar Anarossi Takamitsu Matsubara 60 9 0 14 Oct 2022
Koopman Neural Forecaster for Time Series with Temporal Distribution Shifts Rui Wang Yihe Dong Sercan O. Arik Rose Yu AI4TS 109 28 0 07 Oct 2022
Learning Bilinear Models of Actuated Koopman Generators from Partially-Observed Trajectories Samuel E. Otto Sebastian Peitz C. Rowley 84 19 0 20 Sep 2022
Gaussian Process Koopman Mode Decomposition Takahiro Kawashima H. Hino 46 7 0 09 Sep 2022
Data-driven End-to-end Learning of Pole Placement Control for Nonlinear Dynamics via Koopman Invariant Subspaces Tomoharu Iwata Yoshinobu Kawahara 46 3 0 16 Aug 2022
Temporal Forward-Backward Consistency, Not Residual Error, Measures the Prediction Accuracy of Extended Dynamic Mode Decomposition Masih Haseli Jorge Cortes 87 15 0 15 Jul 2022
Stable Invariant Models via Koopman Spectra Takuya Konishi Yoshinobu Kawahara 72 3 0 15 Jul 2022
Heterogeneous mixtures of dictionary functions to approximate subspace invariance in Koopman operators Charles A. Johnson Shara Balakrishnan Enoch Yeung 24 2 0 27 Jun 2022
Transformer for Partial Differential Equations' Operator Learning Zijie Li Kazem Meidani A. Farimani 117 172 0 26 May 2022
Neural ODEs with Irregular and Noisy Data P. Goyal P. Benner 56 4 0 19 May 2022
Assessment of convolutional recurrent autoencoder network for learning wave propagation Wrik Mallik R. Jaiman J. Jelovica BDL 24 1 0 12 Apr 2022
When Physics Meets Machine Learning: A Survey of Physics-Informed Machine Learning Chuizheng Meng Sungyong Seo Defu Cao Sam Griesemer Yan Liu PINN AI4CE 122 59 0 31 Mar 2022
Can A Neural Network Hear the Shape of A Drum? Yueqi Zhao M. Fogler 46 1 0 14 Mar 2022
Predicting the temporal dynamics of turbulent channels through deep learning Giuseppe Borrelli L. Guastoni Hamidreza Eivazi P. Schlatter Ricardo Vinuesa AI4TS 82 18 0 02 Mar 2022
E-LMC: Extended Linear Model of Coregionalization for Spatial Field Prediction Shihong Wang Xueying Zhang Yichen Meng W. Xing 49 1 0 01 Mar 2022
Bounded nonlinear forecasts of partially observed geophysical systems with physics-constrained deep learning Said Ouala Steven L. Brunton A. Pascual Bertrand Chapron F. Collard L. Gaultier Ronan Fablet PINN AI4TS AI4CE 71 10 0 11 Feb 2022
Discovering Governing Equations from Partial Measurements with Deep Delay Autoencoders Joseph Bakarji Kathleen P. Champion J. Nathan Kutz Steven L. Brunton 111 86 0 13 Jan 2022
Multiway Ensemble Kalman Filter Yu Wang Alfred Hero 56 1 0 08 Dec 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
ACD-EDMD: Analytical Construction for Dictionaries of Lifting Functions in Koopman Operator-based Nonlinear Robotic Systems Lu Shi Konstantinos Karydis 127 27 0 24 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
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 186 385 0 05 Oct 2021
Applying Machine Learning to Study Fluid Mechanics Steven L. Brunton PINN AI4CE 63 100 0 05 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
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
Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling Franck Djeumou Cyrus Neary Eric Goubault S. Putot Ufuk Topcu PINN AI4CE 101 73 0 14 Sep 2021
Stochastic Adversarial Koopman Model for Dynamical Systems K. Balakrishnan Devesh Upadhyay 45 8 0 10 Sep 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 60 15 0 08 Aug 2021
Discovering Sparse Interpretable Dynamics from Partial Observations Peter Y. Lu Joan Ariño Bernad Marin Soljacic AI4CE 83 25 0 22 Jul 2021
Physics-Guided Deep Learning for Dynamical Systems: A Survey Rui Wang Rose Yu AI4CE PINN 115 69 0 02 Jul 2021
Innovations Autoencoder and its Application in One-class Anomalous Sequence Detection Xinyi Wang Lang Tong BDL AI4TS 48 12 0 23 Jun 2021