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Recurrent Neural Networks for Dynamical Systems: Applications to
  Ordinary Differential Equations, Collective Motion, and Hydrological Modeling

Recurrent Neural Networks for Dynamical Systems: Applications to Ordinary Differential Equations, Collective Motion, and Hydrological Modeling

14 February 2022
Yonggi Park
Kelum Gajamannage
D. Jayathilake
Erik Bollt
    AI4CE
ArXivPDFHTML

Papers citing "Recurrent Neural Networks for Dynamical Systems: Applications to Ordinary Differential Equations, Collective Motion, and Hydrological Modeling"

5 / 5 papers shown
Title
Modeling Nonlinear Oscillator Networks Using Physics-Informed Hybrid Reservoir Computing
Modeling Nonlinear Oscillator Networks Using Physics-Informed Hybrid Reservoir Computing
Andrew Shannon
Conor Houghton
David Barton
Martin Homer
23
0
0
07 Nov 2024
Learning Interpretable Hierarchical Dynamical Systems Models from Time Series Data
Learning Interpretable Hierarchical Dynamical Systems Models from Time Series Data
Manuel Brenner
Elias Weber
G. Koppe
Daniel Durstewitz
AI4TS
AI4CE
44
4
0
07 Oct 2024
Physics-informed Convolutional Recurrent Surrogate Model for Reservoir
  Simulation with Well Controls
Physics-informed Convolutional Recurrent Surrogate Model for Reservoir Simulation with Well Controls
Jungang Chen
Eduardo Gildin
John E. Killough
AI4CE
29
6
0
15 May 2023
On the effectiveness of neural priors in modeling dynamical systems
On the effectiveness of neural priors in modeling dynamical systems
Sameera Ramasinghe
Hemanth Saratchandran
Violetta Shevchenko
Simon Lucey
29
2
0
10 Mar 2023
Constructing coarse-scale bifurcation diagrams from spatio-temporal
  observations of microscopic simulations: A parsimonious machine learning
  approach
Constructing coarse-scale bifurcation diagrams from spatio-temporal observations of microscopic simulations: A parsimonious machine learning approach
Evangelos Galaris
Gianluca Fabiani
I. Gallos
Ioannis G. Kevrekidis
Constantinos Siettos
AI4CE
23
40
0
31 Jan 2022
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