GitHub - casus/PDE-Learning: Learning Partial Differential Equations by Spectral Approximates of General Sobolev Spaces

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Learning Partial Differential Equations by Spectral Approximates of General Sobolev Spaces

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Name		Name	Last commit message	Last commit date
Latest commit History 12 Commits
PSM_V1		PSM_V1
PSM_V2		PSM_V2
NavierStokesEquation_Inverse_Problem.ipynb		NavierStokesEquation_Inverse_Problem.ipynb
PoissonEquation-Inverse_Problem.ipynb		PoissonEquation-Inverse_Problem.ipynb
PoissonEquation2D_H^k.ipynb		PoissonEquation2D_H^k.ipynb
PoissonEquation4D.ipynb		PoissonEquation4D.ipynb
PoissonEquation_Forward_Problem.ipynb		PoissonEquation_Forward_Problem.ipynb
QHOEquation-Forward_Problem_m=31.ipynb		QHOEquation-Forward_Problem_m=31.ipynb
QHOEquation_Forward_Problem_m=21.ipynb		QHOEquation_Forward_Problem_m=21.ipynb
QHOEquation_Inverse_Problem.ipynb		QHOEquation_Inverse_Problem.ipynb
README.txt		README.txt

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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 : [email protected], under the supervision of:
  - Juan-Esteban Suarez : [email protected]
  - Dr. Michael Hecht : [email protected]
All members of the Center for Advanced Systems Understanding (CASUS)