implement non-parametric HMMs
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help wanted
- Dominant language
- Python
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Description
Implement some of the hierarchical dirichlet process HDP-HMM algorithms from https://github.com/mattjj/pyhsmm
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
Begin with the linked pyhsmm repository and compare its hierarchical Dirichlet process HMM algorithms with Dynamax's existing state-space and hidden Markov model functionality. Identify which HDP-HMM algorithms are in scope and where they belong in this Python/JAX package; done means the selected algorithms are implemented and their behavior is validated.
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
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100