Article

PINN Training Using Biobjective Optimization: The Trade-Off between Data Loss and Residual Loss

2022-06-14

Abstract excerpt

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. In this paper, we suggest a multiobjective perspective on the training of PINNs by treating the data loss and the residual loss as two individual objective functions in a truly biobjective optimizat...

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Literature Corpus work: 6a2c2612-0f0b-50ee-ae7a-c93a1335b776
DOI: 10.2139/ssrn.4134903

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