Expanding samplers included in numpyro
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- Dominant language
- Python
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Description
Techniques like SMC, Langevin sampling and MALA don't seem to be covered by numpyro out of the box. I am aware that using blackjax or TFP with an adapter is an option in some cases, but still feel that a numpyro-native implementation could lower the barrier to using a wider range of samplers and make modelling code more concise and self-contained. Would you be open to accepting contributions that implement these missing samplers? If positive in principle, very happy to discuss case by case here or in separate issues.
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
The issue names no files, tests, or entry points. First clarify which sampler—SMC, Langevin sampling, or MALA—is in scope and what maintainers would accept; completion would require a separately scoped NumPyro-native sampler contribution with appropriate project validation.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Quiet
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100