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The Neural Network shifted-Proper Orthogonal Decomposition: a Machine
  Learning Approach for Non-linear Reduction of Hyperbolic Equations
v1v2 (latest)

The Neural Network shifted-Proper Orthogonal Decomposition: a Machine Learning Approach for Non-linear Reduction of Hyperbolic Equations

14 August 2021
Davide Papapicco
N. Demo
M. Girfoglio
G. Stabile
G. Rozza
ArXiv (abs)PDFHTML

Papers citing "The Neural Network shifted-Proper Orthogonal Decomposition: a Machine Learning Approach for Non-linear Reduction of Hyperbolic Equations"

11 / 11 papers shown
Title
Artificial Geographically Weighted Neural Network: A Novel Framework for Spatial Analysis with Geographically Weighted Layers
Artificial Geographically Weighted Neural Network: A Novel Framework for Spatial Analysis with Geographically Weighted Layers
Jianfei Cao
Dongchao Wang
33
0
0
01 Apr 2025
GoRINNs: Godunov-Riemann Informed Neural Networks for Learning
  Hyperbolic Conservation Laws
GoRINNs: Godunov-Riemann Informed Neural Networks for Learning Hyperbolic Conservation Laws
Dimitrios G. Patsatzis
Mario di Bernardo
L. Russo
Constantinos Siettos
AI4CE
41
2
0
29 Oct 2024
Distributed computing for physics-based data-driven reduced modeling at scale: Application to a rotating detonation rocket engine
Distributed computing for physics-based data-driven reduced modeling at scale: Application to a rotating detonation rocket engine
Ionut-Gabriel Farcas
Rayomand P. Gundevia
R. Munipalli
Karen E. Willcox
AI4CE
120
1
0
13 Jul 2024
TGPT-PINN: Nonlinear model reduction with transformed GPT-PINNs
TGPT-PINN: Nonlinear model reduction with transformed GPT-PINNs
Yanlai Chen
Yajie Ji
A. Narayan
Zhenli Xu
PINN
67
4
0
06 Mar 2024
CoLoRA: Continuous low-rank adaptation for reduced implicit neural
  modeling of parameterized partial differential equations
CoLoRA: Continuous low-rank adaptation for reduced implicit neural modeling of parameterized partial differential equations
Jules Berman
Benjamin Peherstorfer
91
10
0
22 Feb 2024
Symplectic model reduction of Hamiltonian systems using data-driven
  quadratic manifolds
Symplectic model reduction of Hamiltonian systems using data-driven quadratic manifolds
Harsh Sharma
Hongliang Mu
Patrick Buchfink
R. Geelen
Silke Glas
Boris Kramer
75
28
0
24 May 2023
A DeepONet multi-fidelity approach for residual learning in reduced
  order modeling
A DeepONet multi-fidelity approach for residual learning in reduced order modeling
N. Demo
M. Tezzele
G. Rozza
79
21
0
24 Feb 2023
Towards a machine learning pipeline in reduced order modelling for
  inverse problems: neural networks for boundary parametrization,
  dimensionality reduction and solution manifold approximation
Towards a machine learning pipeline in reduced order modelling for inverse problems: neural networks for boundary parametrization, dimensionality reduction and solution manifold approximation
A. Ivagnes
N. Demo
G. Rozza
MedImAI4CE
57
8
0
26 Oct 2022
A Continuous Convolutional Trainable Filter for Modelling Unstructured
  Data
A Continuous Convolutional Trainable Filter for Modelling Unstructured Data
Dario Coscia
L. Meneghetti
N. Demo
G. Stabile
G. Rozza
69
8
0
24 Oct 2022
SVD Perspectives for Augmenting DeepONet Flexibility and
  Interpretability
SVD Perspectives for Augmenting DeepONet Flexibility and Interpretability
Simone Venturi
T. Casey
131
42
0
27 Apr 2022
Non-linear manifold ROM with Convolutional Autoencoders and Reduced
  Over-Collocation method
Non-linear manifold ROM with Convolutional Autoencoders and Reduced Over-Collocation method
F. Romor
G. Stabile
G. Rozza
82
23
0
01 Mar 2022
1