On the Complexity of Identification in Linear Structural Causal Models
Authors: Julian Dörfler, Benito van der Zander, Markus Bläser, Maciej Liskiewicz
NeurIPS 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | This is a purely theory based paper with no experiments. No data sets were used. No crowdsourcing or contract work was done. |
| Researcher Affiliation | Academia | Julian D orfler Saarland University Benito van der Zander University of L ubeck Markus Bl aser Saarland University Maciej Li skiewicz University of L ubeck |
| Pseudocode | No | The paper does not contain structured pseudocode or algorithm blocks (clearly labeled algorithm sections or code-like formatted procedures). |
| Open Source Code | No | The paper does not provide concrete access to source code (specific repository link, explicit code release statement, or code in supplementary materials) for the methodology described in this paper. |
| Open Datasets | No | This paper does not contain experimental results. |
| Dataset Splits | No | The paper does not include experiments. |
| Hardware Specification | No | The paper does not include experiments. |
| Software Dependencies | No | The paper does not specify any software dependencies with version numbers for experimental reproducibility as it does not include experiments. |
| Experiment Setup | No | The paper does not include experiments. |