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Geodesic convolutional neural networks on Riemannian manifolds

Geodesic convolutional neural networks on Riemannian manifolds

26 January 2015
Jonathan Masci
Davide Boscaini
M. Bronstein
P. Vandergheynst
ArXivPDFHTML

Papers citing "Geodesic convolutional neural networks on Riemannian manifolds"

7 / 7 papers shown
Title
Flow-based Generative Models for Learning Manifold to Manifold Mappings
Flow-based Generative Models for Learning Manifold to Manifold Mappings
Xingjian Zhen
Rudrasis Chakraborty
Liu Yang
Vikas Singh
DRL
MedIm
19
9
0
18 Dec 2020
HexagDLy - Processing hexagonally sampled data with CNNs in PyTorch
HexagDLy - Processing hexagonally sampled data with CNNs in PyTorch
C. Steppa
T. Holch
11
37
0
05 Mar 2019
Parallel Transport Convolution: A New Tool for Convolutional Neural
  Networks on Manifolds
Parallel Transport Convolution: A New Tool for Convolutional Neural Networks on Manifolds
Stefan C. Schonsheck
Bin Dong
Rongjie Lai
16
22
0
21 May 2018
Learning quadrangulated patches for 3D shape parameterization and
  completion
Learning quadrangulated patches for 3D shape parameterization and completion
Kripasindhu Sarkar
Kiran Varanasi
D. Stricker
3DV
11
24
0
20 Sep 2017
Convolutional Neural Networks on Graphs with Fast Localized Spectral
  Filtering
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering
M. Defferrard
Xavier Bresson
P. Vandergheynst
GNN
8
7,567
0
30 Jun 2016
Learning shape correspondence with anisotropic convolutional neural
  networks
Learning shape correspondence with anisotropic convolutional neural networks
Davide Boscaini
Jonathan Masci
Emanuele Rodolà
M. Bronstein
3DPC
13
505
0
20 May 2016
Molecular Graph Convolutions: Moving Beyond Fingerprints
Molecular Graph Convolutions: Moving Beyond Fingerprints
S. Kearnes
Kevin McCloskey
Marc Berndl
Vijay S. Pande
Patrick F. Riley
GNN
27
1,435
0
02 Mar 2016
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