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Modelling spatiotemporal turbulent dynamics with the convolutional
  autoencoder echo state network
v1v2 (latest)

Modelling spatiotemporal turbulent dynamics with the convolutional autoencoder echo state network

21 November 2022
A. Racca
N. Doan
Luca Magri
ArXiv (abs)PDFHTML

Papers citing "Modelling spatiotemporal turbulent dynamics with the convolutional autoencoder echo state network"

4 / 4 papers shown
Title
Generative Learning for Forecasting the Dynamics of Complex Systems
Generative Learning for Forecasting the Dynamics of Complex Systems
Han Gao
Sebastian Kaltenbach
Petros Koumoutsakos
AI4TSAI4CE
123
8
0
27 Feb 2024
Uncovering solutions from data corrupted by systematic errors: A
  physics-constrained convolutional neural network approach
Uncovering solutions from data corrupted by systematic errors: A physics-constrained convolutional neural network approach
Daniel Kelshaw
Luca Magri
PINN
26
2
0
07 Jun 2023
Short and Straight: Geodesics on Differentiable Manifolds
Short and Straight: Geodesics on Differentiable Manifolds
Daniel Kelshaw
Luca Magri
78
0
0
24 May 2023
Convolutional autoencoder for the spatiotemporal latent representation
  of turbulence
Convolutional autoencoder for the spatiotemporal latent representation of turbulence
N. Doan
A. Racca
Luca Magri
37
3
0
31 Jan 2023
1