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[Do-PFN] In-Context Learning for Causal Effect EstimationCausality/paper 2025. 10. 29. 20:31
https://neurips.cc/virtual/2025/loc/san-diego/poster/118284
NeurIPS Poster Do-PFN: In-Context Learning for Causal Effect Estimation
Causal effect estimation is critical to a range of scientific disciplines. Existing methods for this task either require interventional data, knowledge about the ground-truth causal graph, or rely on assumptions such as unconfoundedness, restricting their
neurips.cc
https://arxiv.org/pdf/2506.06039
(NeurIPS 2025)
https://github.com/jr2021/Do-PFN
GitHub - jr2021/Do-PFN
Contribute to jr2021/Do-PFN development by creating an account on GitHub.
github.com
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