Expectation propagation and approximate Bayesian computation.
Here are X’s comments on a paper, “Expectation-Propagation for Likelihood-Free Inference,” by Simon Barthelme and Nicolas Chopin. The paper is not new but the topic is still hot.
Also there’s this paper by Maurizio Filippone and Mark Girolami on computation for Gaussian process models. I wonder how this connects to GPstuff, which I think is what Aki did to fit the birthdays model:
This stuff is where it’s at.
I added the pseudo marginal likelihood method proposed by Filippone & Girolami to GPstuff todo list right after I had read the paper. It will be useful in some modeling cases with non-Gaussian models, but it is not needed in birthdays model which uses Gaussian model.