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2001.04263
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Deep learning to discover and predict dynamics on an inertial manifold
Physical Review E (PRE), 2019
20 December 2019
Alec J. Linot
M. Graham
AI4CE
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Papers citing
"Deep learning to discover and predict dynamics on an inertial manifold"
37 / 37 papers shown
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Michael D. Graham
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Deep Learning of the Evolution Operator Enables Forecasting of Out-of-Training Dynamics in Chaotic Systems
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Peter H. Haynes
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347
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28 Feb 2025
Learning to Decouple Complex Systems
International Conference on Machine Learning (ICML), 2023
Zihan Zhou
Tianshu Yu
BDL
380
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17 Feb 2025
Inferring stability properties of chaotic systems on autoencoders' latent spaces
Elise Özalp
Luca Magri
235
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Stability analysis of chaotic systems in latent spaces
Nonlinear dynamics (Nonlinear Dyn.), 2024
Elise Özalp
Luca Magri
342
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01 Oct 2024
On instabilities in neural network-based physics simulators
Daniel Floryan
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259
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18 Jun 2024
Data-driven low-dimensional model of a sedimenting flexible fiber
Physical Review Fluids (Phys. Rev. Fluids), 2024
Andrew J Fox
Michael D. Graham
AI4CE
242
4
0
16 May 2024
Generative Learning for Forecasting the Dynamics of Complex Systems
Han Gao
Sebastian Kaltenbach
Petros Koumoutsakos
AI4TS
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412
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27 Feb 2024
A Novel Paradigm in Solving Multiscale Problems
Jing Wang
Zheng Li
Pengyu Lai
Rui Wang
Di Yang
Dewu Yang
Hui Xu
Wenquan Tao
AI4CE
488
1
0
07 Feb 2024
RefreshNet: Learning Multiscale Dynamics through Hierarchical Refreshing
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Junaid Farooq
Danish Rafiq
Pantelis R. Vlachas
M. A. Bazaz
160
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24 Jan 2024
Building symmetries into data-driven manifold dynamics models for complex flows: application to two-dimensional Kolmogorov flow
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Alec J. Linot
Michael D. Graham
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377
3
0
15 Dec 2023
Generative learning for nonlinear dynamics
William Gilpin
AI4CE
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376
53
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07 Nov 2023
Stochastic Latent Transformer: Efficient Modelling of Stochastically Forced Zonal Jets
Journal of Advances in Modeling Earth Systems (JAMES), 2023
Ira J. S. Shokar
R. Kerswell
Peter H. Haynes
248
11
0
25 Oct 2023
Nonlinear dimensionality reduction then and now: AIMs for dissipative PDEs in the ML era
E. D. Koronaki
N. Evangelou
Cristina P. Martin-Linares
E. Titi
Ioannis G. Kevrekidis
235
13
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24 Oct 2023
Enhancing Predictive Capabilities in Data-Driven Dynamical Modeling with Automatic Differentiation: Koopman and Neural ODE Approaches
Chaos (Chaos), 2023
Ricardo Constante-Amores
Alec J. Linot
Michael D. Graham
237
11
0
10 Oct 2023
Interpretable learning of effective dynamics for multiscale systems
Emmanuel Menier
Sebastian Kaltenbach
Mouadh Yagoubi
Marc Schoenauer
Petros Koumoutsakos
AI4CE
244
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11 Sep 2023
Autoencoders for discovering manifold dimension and coordinates in data from complex dynamical systems
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Carlos E. Pérez De Jesús
Andrew J Fox
M. Graham
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398
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01 May 2023
Recurrences reveal shared causal drivers of complex time series
Physical Review X (PRX), 2023
W. Gilpin
CML
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247
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31 Jan 2023
Turbulence control in plane Couette flow using low-dimensional neural ODE-based models and deep reinforcement learning
International Journal of Heat and Fluid Flow (IJHFF), 2023
Alec J. Linot
Kevin Zeng
M. Graham
AI4CE
275
30
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28 Jan 2023
Super-Resolution Analysis via Machine Learning: A Survey for Fluid Flows
Theoretical and Computational Fluid Dynamics (TCFD), 2023
Kai Fukami
K. Fukagata
Kunihiko Taira
AI4CE
389
157
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26 Jan 2023
Dynamics of a data-driven low-dimensional model of turbulent minimal Couette flow
Journal of Fluid Mechanics (JFM), 2023
Alec J. Linot
M. Graham
AI4CE
193
38
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11 Jan 2023
Data-driven low-dimensional dynamic model of Kolmogorov flow
Physical Review Fluids (PRFluids), 2022
Carlos E. Pérez De Jesús
M. Graham
326
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29 Oct 2022
Prospects of federated machine learning in fluid dynamics
AIP Advances (AIP Adv.), 2022
Omer San
Suraj Pawar
Adil Rasheed
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233
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15 Aug 2022
Decentralized digital twins of complex dynamical systems
Scientific Reports (Sci Rep), 2022
Omer San
Suraj Pawar
Adil Rasheed
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190
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07 Jul 2022
Learning effective dynamics from data-driven stochastic systems
Chaos (Chaos), 2022
Lingyu Feng
Ting Gao
Min Dai
Jinqiao Duan
SyDa
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386
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09 May 2022
Data-driven control of spatiotemporal chaos with reduced-order neural ODE-based models and reinforcement learning
Proceedings of the Royal Society A (Proc. R. Soc. A), 2022
Kevin Zeng
Alec J. Linot
M. Graham
AI4CE
265
38
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01 May 2022
Discovering Governing Equations from Partial Measurements with Deep Delay Autoencoders
Proceedings of the Royal Society A (Proc. R. Soc. A), 2022
Joseph Bakarji
Kathleen P. Champion
J. Nathan Kutz
Steven L. Brunton
376
117
0
13 Jan 2022
Symmetry-Aware Autoencoders: s-PCA and s-nlPCA
Simon Kneer
T. Sayadi
D. Sipp
Peter J. Schmid
Georgios Rigas
255
14
0
04 Nov 2021
Nonlinear proper orthogonal decomposition for convection-dominated flows
Shady E. Ahmed
Omer San
Adil Rasheed
T. Iliescu
254
46
0
15 Oct 2021
Data-Driven Reduced-Order Modeling of Spatiotemporal Chaos with Neural Ordinary Differential Equations
Chaos (Chaos), 2021
Alec J. Linot
M. Graham
270
66
0
31 Aug 2021
Data-driven discovery of intrinsic dynamics
D. Floryan
M. Graham
AI4CE
332
109
0
12 Aug 2021
Learning normal form autoencoders for data-driven discovery of universal,parameter-dependent governing equations
M. Kalia
Steven L. Brunton
H. Meijer
C. Brune
J. Nathan Kutz
AI4CE
146
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0
09 Jun 2021
Learning emergent PDEs in a learned emergent space
Felix P. Kemeth
Tom S. Bertalan
Thomas Thiem
Felix Dietrich
S. Moon
C. Laing
Ioannis G. Kevrekidis
AI4CE
180
7
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23 Dec 2020
Using machine-learning modelling to understand macroscopic dynamics in a system of coupled maps
Francesco Borra
Marco Baldovin
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161
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08 Nov 2020
OnsagerNet: Learning Stable and Interpretable Dynamics using a Generalized Onsager Principle
Physical Review Fluids (Phys. Rev. Fluids), 2020
Haijun Yu
Xinyuan Tian
Weinan E
Qianxiao Li
AI4CE
342
56
0
06 Sep 2020
Multiscale Simulations of Complex Systems by Learning their Effective Dynamics
Nature Machine Intelligence (NMI), 2020
Pantelis R. Vlachas
G. Arampatzis
Caroline Uhler
Petros Koumoutsakos
AI4CE
335
189
0
24 Jun 2020
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