i am not sure what you are disagreeing with. chain rule is basic calculus that precedes understanding hessians. my argument is, if you can not understand what the chain rule is, you will not understand more complicated mathematics in ML. do you think i am wrong ?
EDIT: also uncertainty estimation is the stuff of probabalistic approach to ML. i would say that people who do probabalistic ML are quite mathematically capable (at least to my experience)
EDIT: also uncertainty estimation is the stuff of probabalistic approach to ML. i would say that people who do probabalistic ML are quite mathematically capable (at least to my experience)