HMC, RWMH sampling methods tutorial
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Description
We might want to add a comparison oriented tutorial for various sampling algorithms at some point. Two previous tutorials that I find relevant are
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 linked hamiltonian_monte_carlo.py and basic_usage.ipynb examples to understand the proposed HMC and RWMH comparison. Done means a comparison-oriented tutorial covering these sampling methods has been added to the Turing documentation.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- julia, python
- Domain
- documentation, machine-learning
- Issue type
- Documentation
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100