Causal Inference through a Witness Protection Program
Authors: Ricardo Silva, Robin Evans
NeurIPS 2014 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Section 5 contains experiments with synthetic and real data. |
| Researcher Affiliation | Academia | Ricardo Silva Department of Statistical Science and CSML University College London ricardo@stats.ucl.ac.uk Robin Evans Department of Statistics University of Oxford evans@stats.ox.ac.uk |
| Pseudocode | Yes | Algorithm 1: The outline of the Witness Protection Program algorithm. |
| Open Source Code | Yes | R code is available at http://www.homepages.ucl.ac.uk/ ucgtrbd/wpp. |
| Open Datasets | No | The paper uses synthetic data and "influenza data discussed by [9, 18]" obtained from "Mc Donald, Hiu and Tierney", but provides no concrete access information (links, DOIs, or repository names) for public access to this data. |
| Dataset Splits | No | The paper mentions simulating '5000 points per dataset' and '1000 Monte Carlo samples per decision', but does not specify how these samples are split into training, validation, or test sets for reproducibility. |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., GPU/CPU models, processor types) used for running its experiments. |
| Software Dependencies | No | The paper mentions that the method can be implemented using 'Polymake' or 'SCDD for R', and that 'R code is available', but does not provide specific version numbers for these software dependencies. |
| Experiment Setup | Yes | We run simulations at two levels of parameters: β = 0.9, β = 1.1, and the same configuration except for β = β = 1. Results are summarized in Table 3 for the case ϵw = ϵx = ϵy = 0.2, β = 0.9, β = 1.1. |