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A Tailored Convolutional Neural Network for Nonlinear Manifold Learning
  of Computational Physics Data using Unstructured Spatial Discretizations

A Tailored Convolutional Neural Network for Nonlinear Manifold Learning of Computational Physics Data using Unstructured Spatial Discretizations

11 June 2020
John Tencer
Kevin Potter
    AI4CE
ArXivPDFHTML

Papers citing "A Tailored Convolutional Neural Network for Nonlinear Manifold Learning of Computational Physics Data using Unstructured Spatial Discretizations"

2 / 2 papers shown
Title
An AI-based Domain-Decomposition Non-Intrusive Reduced-Order Model for
  Extended Domains applied to Multiphase Flow in Pipes
An AI-based Domain-Decomposition Non-Intrusive Reduced-Order Model for Extended Domains applied to Multiphase Flow in Pipes
C. Heaney
Zef Wolffs
Jón Atli Tómasson
L. Kahouadji
P. Salinas
A. Nicolle
Omar K. Matar
Ionel M. Navon
N. Srinil
Christopher C. Pain
AI4CE
29
21
0
13 Feb 2022
Geometric deep learning on graphs and manifolds using mixture model CNNs
Geometric deep learning on graphs and manifolds using mixture model CNNs
Federico Monti
Davide Boscaini
Jonathan Masci
Emanuele Rodolà
Jan Svoboda
M. Bronstein
GNN
251
1,811
0
25 Nov 2016
1