Port NumPyro introductory examples to Pyro
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- Dominant language
- Python
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Description
NumPyro now has several excellent introductory examples with no direct counterparts in Pyro. Porting one of these to Pyro would be a great way for someone to simultaneously learn more about Bayesian data analysis and make a valuable open source contribution.
If you are reading this and want to give one of them a try, please leave a comment here so that other people are aware of your work and so we can help you get started!
Bonus points if you can modify an example to use variational inference with Pyro's autoguides rather than MCMC while obtaining similar results.
List of examples:
- Bayesian Regression Using NumPyro (@arijc76 - #3006 )
- Bayesian Hierarchical Regression (@JamesTrick)
- Bayesian Imputation
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 comparing the linked NumPyro introductory examples with the corresponding Pyro documentation and existing examples. Choose an unclaimed tutorial, port it to Pyro, and optionally use Pyro autoguides for variational inference. Done means the example is available in Pyro and produces results comparable to the NumPyro version.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- documentation, machine-learning
- Issue type
- Documentation
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100