
Train Interpretable Neural Networks That Accurately Extrapolate from Small Data - ChrisRackauckas
https://www.stochasticlifestyle.com/how-to-train-interpretable-neural-networks-that-accurately-extrapolate-from-small-data/
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vsskanth
Thanks, I've always wondered how one can incorporate some structural knowledge
into machine learning instead of full-on black box.

Is it possible to learn the system without a direct measurement of the states
of the ODE but using its outputs (y) which are a function of the states (xdot
= f(x,u), y = g(x,u)) ?

Is there some criteria like observability that indicates what are the minimum
measurements (ex: number of states) needed to learn a given ODE system ?

