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Code from Parameterized neural ordinary differential equations: applications to computational physics problems
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Version 2
Version 2
16.09.21, 09:40
Version 1
02.09.21, 06:29
dataset
posted on 08.09.2021, 00:33
authored by
Kookjin Lee
,
Eric J. Parish
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Parameterized neural ordinary differential equations: applications to computational physics problems
Proceedings of the Royal Society A: Mathematical, Physical & Engineering Sciences
Categories
Computational Physics
Artificial Intelligence and Image Processing
Keywords
deep learning
autoencoders
machine learning
nonlinear manifolds
model reduction
neural ordinary differential equations
latent-dynamics learning
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CC BY 4.0
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