[FR] Weakly supervised causal representation learning
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Description
Perhaps a bit non-standard for this library, but would causal learn be interested in providing some causal representation learning algorithms which work well on low-level data (pixels, etc)?
Maybe as a start, a weakly supervised CRL algorithm, like the one presented in Brehmer et al (2022)?
I would be interested in contributing if so!
Reference:
Brehmer, J., De Haan, P., Lippe, P., and Cohen, T. Weakly
supervised causal representation learning. arXiv preprint
arXiv:2203.16437, 2022.
Contributor guide
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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 referenced Brehmer et al. (2022) paper and reviewing causal-learn's existing causal representation learning support. The issue names no files, tests, or entry points and does not define an implementation scope; completion would require an agreed algorithm and project integration plan.
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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
- 20/100