Interpretability in SciML requires mechanistic understanding rather than sparsity, and prior knowledge is often essential for interpretable scientific discovery.
Advancing symbolic regression for earth science with a focus on evapotranspiration modeling.npj Climate and Atmospheric Science, 7(1):1–16, December 2024
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On the definition and importance of interpretability in scientific machine learning
Interpretability in SciML requires mechanistic understanding rather than sparsity, and prior knowledge is often essential for interpretable scientific discovery.