Data publication: Inverse-Dirichlet Weighting Enables Reliable Training of Physics Informed Neural Networks

Maddu, Suryanarayana; Sturm, Dominik; Müller, Christian L.; Sbalzarini, Ivo F.

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Data publication: Inverse-Dirichlet Weighting Enables Reliable Training of Physics Informed Neural Networks

Maddu, S.; Sturm, D.; Müller, C. L.; Sbalzarini, I. F.

Scripts and notebooks to reproduce the results presented in the paper "Inverse-Dirichlet Weighting Enables Reliable Training of Physics Informed Neural
Networks", Maddu et al., 2021

Keywords: physics informed neural networks; sobolev training; computational physics; deep learning; data-driven modeling; multi-objective optimization; catastrophic forgetting; active turbulence

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DOI: 10.1088/2632-2153/ac3712 references this (Id 33337) publication
Inverse Dirichlet Weighting Enables Reliable Training of Physics Informed …
ROBIS: 33335 has used this (Id 33337) publication of HZDR-primary research data

Software in external data repository
Publication year 2021
Programming language: Python
System requirements: python, numpy, scipy, sklearn, torch, matplotlib, seaborn, pandas
License: MIT
Hosted on GitHub: Link to location

Permalink: https://www.hzdr.de/publications/Publ-33337