PHSIC against Random Consistency and Its Application in Causal Inference
Authors: Jue Li, Yuhua Qian, Jieting Wang, Saixiong Liu
IJCAI 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experimental results demonstrate that the causal model based on PHSIC performs well compared to other methods in scenarios involving small sample sizes and noisy data, both in real and simulated datasets. |
| Researcher Affiliation | Academia | Jue Li , Yuhua Qian , Jieting Wang and Saixiong Liu Institute of Big Data Science and Industry, Shanxi University, Taiyuan 030006, China |
| Pseudocode | No | The paper does not contain any structured pseudocode or algorithm blocks. |
| Open Source Code | Yes | The main code and supplementary material have been made available online1. 1https://github.com/lijue688/main.git |
| Open Datasets | Yes | We use one real dataset(CEP) and three simulated datasets(SIM, SIM-G, SIM-IN). We compare the methods based on HSIC score (ANM-HSIC), Entropy score (ANM-Entropy), Gaussian score (ANM-Gauss), and empirical Bayesian score (ANM-FN) with our proposed PHSIC score (ANM-PHSIC). The introduction of the above comparison methods can be found in [Mooij et al., 2016]. |
| Dataset Splits | No | The paper does not explicitly provide training/validation/test dataset splits. It only mentions sample sizes for experiments. |
| Hardware Specification | No | The paper does not provide any specific hardware details used for running the experiments. |
| Software Dependencies | No | The paper does not provide specific software dependency details with version numbers. |
| Experiment Setup | Yes | In order to highlight the advantages of our PHSIC, we conducted experiments on 50 samples with the same experimental parameters as the original ANM-MM. KIKO model. we... conducted experiments on 30 samples with the same experimental parameters as the original KIKO model. HANM model. we use four simulated data and four real data. For the first four data (y = ex, y = x, y = sin(x), concrete), we conducted experiments on 6, 7, and 8 causes respectively, and for the last four data (ozon, y = x2, mpgacc, mpg-mpg), we use 2 and 3 causes respectively. Exponential data(y = ex) and concrete data were tested on 50 samples, while others were tested on 30 samples. |