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Uncertainty quantification for physics-informed deep learning

Guo, Mengwu LU and Brune, Christoph (2021) p.47-51
Abstract
The development of physics-informed deep learning is radically changing compu-tational science and engineering, allowing for an effective integration ofphysics-based and datadriven modeling. Deep learning provides a powerful tool forthe
discovery of governing dynamics underneath data and enables nonlinear model-reduction. A Bayesian viewpoint of deep learning is discussed in this chapter towards the quantification of modeling uncertainties in physics-informed deep learning.
Please use this url to cite or link to this publication:
author
and
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
Mathematics: Key Enabling Technology for Scientific Machine Learning
editor
Schilders, W. H. A.
pages
47 - 51
publisher
Dutch Platform for Mathematics
language
English
LU publication?
no
id
282bf84a-a4ab-4fbd-83cc-3d43445f2d50
alternative location
https://platformwiskunde.nl/wp-content/uploads/2021/11/Math_KET_SciML.pdf
date added to LUP
2024-03-23 22:15:09
date last changed
2024-04-17 15:03:42
@misc{282bf84a-a4ab-4fbd-83cc-3d43445f2d50,
  abstract     = {{The development of physics-informed deep learning is radically changing compu-tational science and engineering, allowing for an effective integration ofphysics-based and datadriven modeling. Deep learning provides a powerful tool forthe<br/> discovery of governing dynamics underneath data and enables nonlinear model-reduction. A Bayesian viewpoint of deep learning is discussed in this chapter towards the quantification of modeling uncertainties in physics-informed deep learning.}},
  author       = {{Guo, Mengwu and Brune, Christoph}},
  booktitle    = {{Mathematics: Key Enabling Technology for Scientific Machine Learning}},
  editor       = {{Schilders, W. H. A.}},
  language     = {{eng}},
  pages        = {{47--51}},
  publisher    = {{Dutch Platform for Mathematics}},
  title        = {{Uncertainty quantification for physics-informed deep learning}},
  url          = {{https://platformwiskunde.nl/wp-content/uploads/2021/11/Math_KET_SciML.pdf}},
  year         = {{2021}},
}