https://github.com/casus/pde-learning
Learning Partial Differential Equations by Spectral Approximates of General Sobolev Spaces
Science Score: 26.0%
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Low similarity (3.4%) to scientific vocabulary
Keywords
approximation
inverse-problems
pde-solver
Last synced: 5 months ago
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Learning Partial Differential Equations by Spectral Approximates of General Sobolev Spaces
Basic Info
Statistics
- Stars: 6
- Watchers: 2
- Forks: 2
- Open Issues: 2
- Releases: 0
Topics
approximation
inverse-problems
pde-solver
Created about 3 years ago
· Last pushed over 1 year ago
Metadata Files
Readme
README.txt
This framework contains the results submitted on the paper "Negative Order Sobolev Cubatures: Preconditioners of Partial Differential Equation Learning Tasks Circumventing Numerical Stiffness", submitted to IOP Machine Learning: Science and Technology ArXiv preprint is available, https://doi.org/10.48550/arXiv.2301.04887 The code was developed by Phil-Alexander Hofmann : p.hofmann@hzdr.de, under the supervision of: - Juan-Esteban Suarez : j.suarez-cardona@hzdr.de - Dr. Michael Hecht : m.hecht@hzdr.de All members of the Center for Advanced Systems Understanding (CASUS)
Owner
- Name: Center for Advanced Systems Understanding
- Login: casus
- Kind: organization
- Email: m.bussmann@hzdr.de
- Location: Görlitz, Germany
- Website: www.casus.science
- Repositories: 8
- Profile: https://github.com/casus
Official Github Organization account of the Center for Advanced Systems Understanding
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- Watch event: 1