tensorflow / tensorflow/probability
Feature Request: Maximum A Posteriori (MAP) estimation
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Description
For mixed models, it would be great if MCMC could be initialized with a more accurate estimation. This was a feature in Pymc and Edwardlib, but does not appear to be available in either tensorflow_probability or the edward2.
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 reviewing how MCMC initialization is handled in tensorflow_probability and edward2, then compare the MAP estimation behavior provided by PyMC and Edwardlib. The issue names no files or tests, so first define the expected mixed-model workflow and acceptance criteria before locating an implementation entry point.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- tensorflow
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 30/100