Tutorial or example on embarrassingly parallel/consensus MCMC
Open
@fehiepsi is already working on this.
Since May 12, 2021.
low priority
Tutorials/Examples
- Dominant language
- Python
- Stars
- 2.8k
- Forks
- 315
- Avg merge
- 3d 9h
- Merged PRs (30d)
- 27
Description
Despite that NumPyro is very fast (comparing to other frameworks), running MCMC for large datasets is still slow. Even that GPU helps us increase 10x the speed, it is still slow. This is when subposterior methods show their advantages. It is also a good chance to illustrate some available utilities consensus and parametric, which merge subposteriors together, to users.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Assessment
This issue has not been assessed yet.