Search Results for author: Fabian Heldmann

Found 1 papers, 0 papers with code

PINN Training using Biobjective Optimization: The Trade-off between Data Loss and Residual Loss

no code implementations3 Feb 2023 Fabian Heldmann, Sarah Berkhahn, Matthias Ehrhardt, Kathrin Klamroth

Physics informed neural networks (PINNs) have proven to be an efficient tool to represent problems for which measured data are available and for which the dynamics in the data are expected to follow some physical laws.

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