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SOLIS cracks open the black box of Neural ODEs, extracting interpretable, state-dependent physical parameters from complex nonlinear systems without requiring a pre-defined governing equation.
Finally, a system identification model that gives you both accurate predictions *and* interpretable uncertainty estimates.
You can now get NODE/FODE-level accuracy in system identification *and* understand what the heck is going on inside.