Traditional variational inference fits data using a parameterized distribution family whose members are guaranteed to be normalized.

“Let us plick a group of functions which is always gonna be normalised. And this gives us kind of the like very traditional variation in inference uh problem. Effectively we have a normal distribution with unknown parameters and now we try to fit them onto data.”