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Physics-constrained convolutional neural networks for inverse problems
  in spatiotemporal partial differential equations

Physics-constrained convolutional neural networks for inverse problems in spatiotemporal partial differential equations

18 January 2024
Daniel Kelshaw
Luca Magri
ArXivPDFHTML

Papers citing "Physics-constrained convolutional neural networks for inverse problems in spatiotemporal partial differential equations"

3 / 3 papers shown
Title
Reconstructing unsteady flows from sparse, noisy measurements with a
  physics-constrained convolutional neural network
Reconstructing unsteady flows from sparse, noisy measurements with a physics-constrained convolutional neural network
Yaxin Mo
Luca Magri
AI4CE
20
0
0
30 Aug 2024
Super-resolving sparse observations in partial differential equations: A
  physics-constrained convolutional neural network approach
Super-resolving sparse observations in partial differential equations: A physics-constrained convolutional neural network approach
Daniel Kelshaw
Luca Magri
11
1
0
19 Jun 2023
Real-Time Single Image and Video Super-Resolution Using an Efficient
  Sub-Pixel Convolutional Neural Network
Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network
Wenzhe Shi
Jose Caballero
Ferenc Huszár
J. Totz
Andrew P. Aitken
Rob Bishop
Daniel Rueckert
Zehan Wang
SupR
190
5,173
0
16 Sep 2016
1