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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
Estimating Koopman operators with sketching to provably learn large scale dynamical systems Giacomo Meanti Antoine Chatalic Vladimir Kostic P. Novelli Massimiliano Pontil Lorenzo Rosasco 92 11 0 07 Jun 2023
Generalized Teacher Forcing for Learning Chaotic Dynamics Florian Hess Zahra Monfared Manuela Brenner Daniel Durstewitz AI4CE 259 36 0 07 Jun 2023
DeepGraphDMD: Interpretable Spatio-Temporal Decomposition of Non-linear Functional Brain Network Dynamics Md Asadullah Turja Martin Styner Guorong Wu AI4CE 88 1 0 05 Jun 2023
Fast Dynamic 1D Simulation of Divertor Plasmas with Neural PDE Surrogates Y. Poels G. Derks E. Westerhof Koen Minartz Sven Wiesen Vlado Menkovski 3DGS AI4CE 75 18 0 30 May 2023
Koopa: Learning Non-stationary Time Series Dynamics with Koopman Predictors Yong Liu Chenyu Li Jianmin Wang Mingsheng Long AI4TS 99 121 0 30 May 2023
Discovering Causal Relations and Equations from Data Gustau Camps-Valls Andreas Gerhardus Urmi Ninad Gherardo Varando Georg Martius E. Balaguer-Ballester Ricardo Vinuesa Emiliano Díaz L. Zanna Jakob Runge PINN AI4Cl AI4CE CML 108 77 0 21 May 2023
Learning Linear Embeddings for Non-Linear Network Dynamics with Koopman Message Passing King Fai Yeh Paris D. L. Flood William T. Redman Pietro Lio 69 1 0 15 May 2023
Finite Expression Methods for Discovering Physical Laws from Data Zhongyi Jiang Chunmei Wang Haizhao Yang 66 7 0 15 May 2023
SE(3) Koopman-MPC: Data-driven Learning and Control of Quadrotor UAVs S. Narayanan D. Tellez-Castro S. Sutavani Umesh Vaidya 81 14 0 05 May 2023
Automated Scientific Discovery: From Equation Discovery to Autonomous Discovery Systems Stefan Kramer Mattia Cerrato Jannis Brugger Sašo Džeroski Ross King 90 12 0 03 May 2023
Interpretable Machine Learning for Science with PySR and SymbolicRegression.jl M. Cranmer 122 42 0 02 May 2023
Learning Neural PDE Solvers with Parameter-Guided Channel Attention M. Takamoto Francesco Alesiani Mathias Niepert 111 26 0 27 Apr 2023
On the lifting and reconstruction of nonlinear systems with multiple invariant sets Shaowu Pan Karthik Duraisamy 124 4 0 24 Apr 2023
Automatically identifying ordinary differential equations from data Kevin Egan Weizhen Li Rui Carvalho 37 2 0 21 Apr 2023
Interpretable statistical representations of neural population dynamics and geometry Adam Gosztolai Robert L. Peach Alexis Arnaudon Mauricio Barahona P. Vandergheynst 80 10 0 06 Apr 2023
Convex Optimization-based Policy Adaptation to Compensate for Distributional Shifts Navid Hashemi Justin Ruths Jyotirmoy V. Deshmukh 63 0 0 05 Apr 2023
Multifactor Sequential Disentanglement via Structured Koopman Autoencoders Nimrod Berman Ilana D Naiman Omri Azencot CoGe 89 24 0 30 Mar 2023
Machine Learning for Partial Differential Equations Steven L. Brunton J. Nathan Kutz AI4CE 101 21 0 30 Mar 2023
On the Utility of Koopman Operator Theory in Learning Dexterous Manipulation Skills Yunhai Han Mandy Xie Ye Zhao Harish Ravichandar 96 19 0 23 Mar 2023
Inexact iterative numerical linear algebra for neural network-based spectral estimation and rare-event prediction J. Strahan Spencer C. Guo Chatipat Lorpaiboon Aaron R Dinner Jonathan Weare 133 9 0 22 Mar 2023
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
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 64 5 0 13 Mar 2023
Machine Learning Enhanced Hankel Dynamic-Mode Decomposition Chris Curtis D. J. Alford-Lago Erik Bollt Andrew Tuma 65 10 0 11 Mar 2023
A polar prediction model for learning to represent visual transformations P. Fiquet Eero P. Simoncelli 81 4 0 06 Mar 2023
MetaPhysiCa: OOD Robustness in Physics-informed Machine Learning S Chandra Mouli M. A. Alam Bruno Ribeiro OOD 67 4 0 06 Mar 2023
Learning from Predictions: Fusing Training and Autoregressive Inference for Long-Term Spatiotemporal Forecasts Pantelis R. Vlachas Petros Koumoutsakos AI4TS AI4CE 102 7 0 22 Feb 2023
Koopman-based generalization bound: New aspect for full-rank weights Yuka Hashimoto Sho Sonoda Isao Ishikawa Atsushi Nitanda Taiji Suzuki 54 3 0 12 Feb 2023
IB-UQ: Information bottleneck based uncertainty quantification for neural function regression and neural operator learning Ling Guo Hao Wu Wenwen Zhou Yan Wang Tao Zhou UQCV 68 12 0 07 Feb 2023
Deep networks for system identification: a Survey G. Pillonetto Aleksandr Aravkin Daniel Gedon L. Ljung Antônio H. Ribeiro Thomas B. Schon OOD 107 45 0 30 Jan 2023
Reduced-Order Autodifferentiable Ensemble Kalman Filters Yuming Chen D. Sanz-Alonso Rebecca Willett 71 10 0 27 Jan 2023
Learning Dynamical Systems from Data: A Simple Cross-Validation Perspective, Part V: Sparse Kernel Flows for 132 Chaotic Dynamical Systems L. Yang Xiuwen Sun B. Hamzi H. Owhadi Nai-ming Xie 91 20 0 24 Jan 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
Discover governing differential equations from evolving systems Yuan Li K. Wu Jing Liu 85 8 0 19 Jan 2023
Data-Driven Encoding: A New Numerical Method for Computation of the Koopman Operator Jerry Ng H. Asada 66 4 0 16 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
Integrating Multimodal Data for Joint Generative Modeling of Complex Dynamics Manuela Brenner Florian Hess G. Koppe Daniel Durstewitz 297 11 0 15 Dec 2022
Learning Invariant Subspaces of Koopman Operators--Part 2: Heterogeneous Dictionary Mixing to Approximate Subspace Invariance Charles A. Johnson Shara Balakrishnan Enoch Yeung 41 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 29 1 0 14 Dec 2022
Phase2vec: Dynamical systems embedding with a physics-informed convolutional network Matthew Ricci Noa Moriel Zoe Piran Mor Nitzan AI4CE 101 5 0 07 Dec 2022
Estimation of fibre architecture and scar in myocardial tissue using electrograms: an in-silico study Konstantinos Ntagiantas E. Pignatelli N. Peters C. Cantwell R. Chowdhury Anil A. Bharath 79 2 0 06 Dec 2022
Learning Integrable Dynamics with Action-Angle Networks Ameya Daigavane Arthur Kosmala M. Cranmer Tess E. Smidt S. Ho PINN AI4CE 55 2 0 24 Nov 2022
Exploring Physical Latent Spaces for High-Resolution Flow Restoration Chloé Paliard Nils Thuerey Kiwon Um AI4CE 111 0 0 21 Nov 2022
L-MAE: Masked Autoencoders are Semantic Segmentation Datasets Augmenter Jiaru Jia Ming-Yuan Liu Jiake Xie Xin Chen Hong Zhang Xin Jiang Aiqing Yang 84 0 0 21 Nov 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
Meta-Learning of Neural State-Space Models Using Data From Similar Systems Ankush Chakrabarty Gordon Wichern C. Laughman 86 12 0 14 Nov 2022
Reduced order modeling of parametrized systems through autoencoders and SINDy approach: continuation of periodic solutions Paolo Conti G. Gobat S. Fresca Andrea Manzoni A. Frangi AI4CE 90 51 0 13 Nov 2022
SPADE4: Sparsity and Delay Embedding based Forecasting of Epidemics Esha Saha L. Ho Giang Tran 87 5 0 11 Nov 2022