Interpretability in SciML requires mechanistic understanding rather than sparsity, and prior knowledge is often essential for interpretable scientific discovery.
Distilling Free-Form Natural Laws from Experimental Data.Science, 324(5923):81–85, April 2009
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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.