-
Notifications
You must be signed in to change notification settings - Fork 22
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
log marginal likelihood objective and posterior GP #241
Comments
There's nothing to stop us doing this. It obviously can't be part of any of the AbstractGPs APIs, but that's not to say we shouldn't add a special case thing for
Do you have a particular concern? |
I was thinking about this again in the context of approximate inference. I think I would be in favour of adding a function called
It's also quite clear what What do you think @st-- ? |
When preparing #240 I stumbled across having to pass both FiniteGP for input features
f(x)
and targetsy
to bothposterior
(for PosteriorGP) andlogpdf
(for log marginal likelihood). Maybe the answer is no, but should we have something likelogpdf(::PosteriorGP)
?Also, is it sufficiently intuitive that you get the log marginal likelihood by calling logpdf? why would calling the probability density function return what we get when we integrate out the uncertainty over the GP?
The text was updated successfully, but these errors were encountered: