# Neural Linear Models with Functional Gaussian Process Priors

###### tags: `papers`, `nlm`

Idea: Adding functional priors and using fVI (note: I saw fPOVI in another paper), we get BNN-like uncertainty using NLMs

Questions/Technicalities:

- Prior choice is hard? Why use an uninformative prior when we have other methods
- Brings complexity up - Quadratric -> Cubic in worse case. Probably should not proceed with this approach.