[modeless]

Wow, it is really surprising to me that bezier curve control points produced by an optimization process would be good inputs to a neural net model. Small perturbations to the inputs could produce radically different bezier control points depending on the decisions made by the curve optimizer, so this forces the neural network to learn about the characteristics of the optimizer as well as the input.

Neural nets usually thrive on raw high dimensional inputs, so dramatically reducing the dimensionality of the input seems like a strange decision. I'm sure it improves speed, but I would expect higher accuracy by processing the raw input.

[nielsbot]

I don't know ML, but I was surprised too, since converting a series of points into Bezier paths of a certain degree seems arbitrary...