I'm questioning the association of a single maximum likelihood parameter estimation via analytical optimization as ML, because it does not invole any methods beyond calculus and no models other than the system itself, whose parameters we are estimating.
Perhaps I'm wrong, but the power of NN is in an unknown intermediate representation between the data (measurements in estimation) and the prediction. EKF has no such black box.
Which now that I've written it agrees with top level comment so I rescind my question.
I'm questioning the association of a single maximum likelihood parameter estimation via analytical optimization as ML, because it does not invole any methods beyond calculus and no models other than the system itself, whose parameters we are estimating.
Perhaps I'm wrong, but the power of NN is in an unknown intermediate representation between the data (measurements in estimation) and the prediction. EKF has no such black box.
Which now that I've written it agrees with top level comment so I rescind my question.