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Implement the gID algorithm #72

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cthoyt opened this issue Jun 30, 2021 · 0 comments
Open

Implement the gID algorithm #72

cthoyt opened this issue Jun 30, 2021 · 0 comments
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algorithm project:ASKEM

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@cthoyt
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cthoyt commented Jun 30, 2021 •
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General Identifiability with Arbitrary Surrogate Experiments
S. Lee, J. Correa, E. Bareinboim.
UAI-19. In Proceedings of the 35th Conference on Uncertainty in Artificial Intelligence, 2019.
Columbia CausalAI Laboratory, Technical Report (R-46), May, 2019. [pdf, errata, bib]

The paper does not appear to describe a related gIDC algorithm that extend gID to conditional datasets.
@cthoyt cthoyt mentioned this issue Jun 30, 2021
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@cthoyt cthoyt mentioned this issue Nov 1, 2022
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@cthoyt cthoyt mentioned this issue Aug 7, 2023
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cthoyt added a commit that referenced this issue Aug 29, 2023
@cthoyt
Implement sigma-separation (#150)
92df010 
Closes #120

This PR adds a high-level interface and implements tests for
sigma-separation, a generalization of d-separation that works not only
for directed acyclic graphs, but also for directed graphs containing
cycles. It was originally introduced in

> Constraint-based Causal Discovery for Non-Linear Structural Causal
Models with Cycles and Latent Confounders
> Forré and Mooij. 2019.
[arXiv:1807.03024](https://arxiv.org/abs/1807.03024)

and is an integral part of cyclic ID algorithm (see
#71) and the gID
algorithm (see #72)

## References/Notes

-
https://stats.stackexchange.com/questions/586810/sigma-separation-question-in-cyclic-causal-graph-understanding-sigma-separatio
- Author's implementation: https://github.com/caus-am/sigmasep
@cthoyt cthoyt pinned this issue Aug 29, 2023
@cthoyt cthoyt mentioned this issue Jan 26, 2024
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