TuringLang / TuringLang/AbstractMCMC.jl
Consider transfering the `ESSModel` to `AbstractMCMC`
Nobody has claimed this yet.
- Dominant language
- Julia
- Stars
- 108
- Forks
- 20
- PR merge metrics
- No merged PRs in 30d
Description
We currently have a type ESSModel that implements a factorised version of logdensityproblem.
Now that we have the following new type, does it make sense to generalise and transfer the ESSModel type into this package?
In addition, this factorisation is also helpful for other samplers like nested sampling (see NestedModel) and tempering methods (e.g. when we only temper the likelihood term).
cc @torfjelde @devmotion @mileslucas
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.
Research direction
Start by reading the referenced ESSModel in EllipticalSliceSampling.jl's src/model.jl and the LogDensityProblem types in AbstractMCMC.jl's src/logdensityproblems.jl. Compare the related NestedModel in NestedSamplers.jl, then determine the shared factorisation interface and what transferring and generalising ESSModel would require across these samplers.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- julia
- Domain
- backend-api-design
- Issue type
- Refactor
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100