https://github.com/jwallwork23/nn_adapt
Accelerating goal-oriented error estimation using neural networks
https://github.com/jwallwork23/nn_adapt
deep-learning error-estimation mesh-adaptation neural-network python
Last synced: 4 months ago
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Accelerating goal-oriented error estimation using neural networks
- Host: GitHub
- URL: https://github.com/jwallwork23/nn_adapt
- Owner: jwallwork23
- Created: 2021-11-17T11:23:20.000Z (about 4 years ago)
- Default Branch: main
- Last Pushed: 2022-09-09T10:42:50.000Z (over 3 years ago)
- Last Synced: 2023-03-06T15:21:25.953Z (almost 3 years ago)
- Topics: deep-learning, error-estimation, mesh-adaptation, neural-network, python
- Language: Python
- Homepage:
- Size: 649 KB
- Stars: 0
- Watchers: 2
- Forks: 1
- Open Issues: 6
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Metadata Files:
- Readme: README.md
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README
# Accelerating goal-oriented error estimation using artificial neural networks
This repo emulates the error estimation step for anisotropic
goal-oriented mesh adaptation using artificial neural networks.
This is research of the Applied Modelling and Computation Group
([AMCG]) at Imperial College London.
#### For feedback, comments and questions, please email j.wallwork16@imperial.ac.uk.
[AMCG]: http://www.imperial.ac.uk/earth-science/research/research-groups/amcg/ "AMCG"