PyCC.id packages a hypothesis-driven method using identifiable ODE skeletons for equation discovery from data, supporting multiple paradigms like neural networks and sparse regression.
Integrating prior knowledge in equation discovery: Interpretable symmetry- informed neural networks and symbolic regression via characteristic curves
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PyCC.id: A package for hypothesis-driven equation discovery with structural identifiability
PyCC.id packages a hypothesis-driven method using identifiable ODE skeletons for equation discovery from data, supporting multiple paradigms like neural networks and sparse regression.