vdblm / CausalPFN
CausalPFN: Amortized Causal Effect Estimation via In-Context Learning
Why this job: works in the areas we cover, but does not say which job it does
What it does
- Fast Inference. Amortized learning enables rapid causal effect estimation without retraining
- Uncertainty Quantification. Built-in calibration and confidence estimation
- GPU Accelerated. Optimized for modern hardware with CUDA support
- Benchmarked. Competitive performance against state-of-the-art causal inference methods
- Uplift-Modelling. Supports treatment effect estimation for personalized decision-making in real-world applications
Get started
No single install command. Read the steps in the README (opens in new tab)
- Maintenance
- Active
- Last commit 46 days ago
- Stars
- 141
- +4 this week
- Licence
- Apache-2.0
- Allows business use
- Downloads for
- None listed
- No release files
- Latest version
- v0.1.5
- Released 46 days ago
- Built with
- Jupyter Notebook
- 81% of the code
Is it looked after?
- Contributors
- Not stated
- Last 90 days
- Issues
- 83% closed
- 1 still open
- Pull requests
- 10 merged
- 1 waiting
- Releases
- 1
- 1 in the last year
- No contributing guide
- No security policy
- No code of conduct
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More: languages, topics and project record
Languages
- Jupyter Notebook 81%
- Python 19%
Topics
- causal-inference
- causalpfn
- foundation-models
- machine-learning
Project record
- JobOther AI tools
- StatusListed
- Commits38
- Forks16
- Watching3
- Stars in 28 days+7
- CreatedJun 9, 2025
- First seen by usNov 7, 2026
- CheckedNov 8, 2026