Hi,
I was wondering if any repo’s or notebooks are in the eco-system which use PyTorch to demonstrate theory, rather than do experiments, (although the border between the two is a bit vague).
There’s a lot of beautiful theory on function approximation, for example,
Learning Real and Boolean Functions: When Is Deep Better Than Shallow 24
is quite readable.
I think it builds on Vapnik–Chervonenkis theory 7.
@smth - Vladimir Vapnik is at FAIR now, (I think)? So I guess there might be some, “in house teaching courses”, that covers statistical learning theory, and is implemented using PyTorch?
@apaszke, @fmassa is this something you guys would be interested in? Or, is the focus of PyTorch more leaning towards experiments/applications?