PyCC.id: A package for hypothesis-driven equation discovery with structural identifiability

In three linesPyCC.id is a Python library for hypothesis-driven equation discovery from time-series data. It uses structural skeletons inspired by characteristic curves to constrain the inverse problem and verify structural identifiability of candidate ODE models. Supports neural networks, symbolic regression, and sparse regression paradigms.

Summary generated by Claude — human-verified