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Translating Numerical Concepts for PDEs into Neural Architectures
v1v2 (latest)

Translating Numerical Concepts for PDEs into Neural Architectures

Scale Space and Variational Methods in Computer Vision (SSVM), 2021
29 March 2021
Tobias Alt
Pascal Peter
Joachim Weickert
Karl Schrader
ArXiv (abs)PDFHTML

Papers citing "Translating Numerical Concepts for PDEs into Neural Architectures"

5 / 5 papers shown
Quantized Convolutional Neural Networks Through the Lens of Partial
  Differential Equations
Quantized Convolutional Neural Networks Through the Lens of Partial Differential EquationsResearch in the Mathematical Sciences (Res. Math. Sci.), 2021
Ido Ben-Yair
Gil Ben Shalom
Moshe Eliasof
Eran Treister
MQ
364
5
0
31 Aug 2021
Designing Rotationally Invariant Neural Networks from PDEs and
  Variational Methods
Designing Rotationally Invariant Neural Networks from PDEs and Variational MethodsResearch in the Mathematical Sciences (Res. Math. Sci.), 2021
Tobias Alt
Karl Schrader
Joachim Weickert
Pascal Peter
M. Augustin
335
4
0
31 Aug 2021
Connections between Numerical Algorithms for PDEs and Neural Networks
Connections between Numerical Algorithms for PDEs and Neural NetworksJournal of Mathematical Imaging and Vision (JMIV), 2021
Tobias Alt
Karl Schrader
M. Augustin
Pascal Peter
Joachim Weickert
PINN
306
30
0
30 Jul 2021
Distributed Multigrid Neural Solvers on Megavoxel Domains
Distributed Multigrid Neural Solvers on Megavoxel DomainsInternational Conference for High Performance Computing, Networking, Storage and Analysis (SC), 2021
Aditya Balu
Sergio Botelho
Biswajit Khara
Vinay Rao
Chinmay Hegde
Soumik Sarkar
Santi S. Adavani
A. Krishnamurthy
Baskar Ganapathysubramanian
AI4CE
338
11
0
29 Apr 2021
PDE-based Group Equivariant Convolutional Neural Networks
PDE-based Group Equivariant Convolutional Neural NetworksJournal of Mathematical Imaging and Vision (JMIV), 2020
B. Smets
J. Portegies
Erik J. Bekkers
R. Duits
AI4CE
668
69
0
24 Jan 2020
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