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

31 citations · 31 across the 1 of their papers we have counts for

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1 paper

cs.LG2023★ 31 cited

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

Fabian Heldmann, Sarah Berkhahn, Matthias Ehrhardt +1

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…