Legendre-polynomial weight parameterization lowers training cost and improves stability in continuous-time network surrogates, but the reported accuracy advantage conflicts with the paper's own error table.
The Innovat ion Energy 2(2), 100087–1 (2025)
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Weight-Parameterization in Continuous Time Deep Neural Networks for Surrogate Modeling
Legendre-polynomial weight parameterization lowers training cost and improves stability in continuous-time network surrogates, but the reported accuracy advantage conflicts with the paper's own error table.