> That would be nonparametric statistics.

No, it wouldn't. Firstly, nonparametrics in general can be a little misleading. The most common instantiations place function ("process") priors on modeling decisions that are otherwise found through trial and error. Those process priors do have their own parameters though. But more importantly, LSTMs and neural networks are very much parametric - their success come from the advances in computing and optimization that have enabled estimating these parameters in very complicated model structures.