Explaining Graph Neural Networks via Structure-aware Interaction Index
Authors: Ngoc Bui, Hieu Trung Nguyen, Viet Anh Nguyen, Rex Ying
ICML 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Extensive experiments on various graph datasets and models demonstrate that our method consistently provides superior subgraph explanations compared to state-of-the-art methods. |
| Researcher Affiliation | Collaboration | 1Yale University 2Vin AI Research 3The Chinese University of Hong Kong. |
| Pseudocode | Yes | Algorithm 1 Permutation-based sampling algorithm for the k-order Myerson-Taylor index. Algorithm 2 Value of an interaction-restricted function (f|E(T)). |
| Open Source Code | Yes | Our implementation is available at: https://github. com/ngocbh/MAGE/ |
| Open Datasets | Yes | We use ten datasets commonly used in the graph explainability literature, including synthetic data, biological, text, and image data. For synthetic datasets, we use Ba-2Motifs (Luo et al., 2020), BA-House Grid (Amara et al., 2023), and SPMotif (Wu et al., 2022) for classification tasks |
| Dataset Splits | Yes | We split the dataset into training, validation, and test subsets with respective ratios of 0.8, 0.1, and 0.1. |
| Hardware Specification | No | The paper does not provide specific details about the hardware (e.g., GPU/CPU models, memory specifications) used to run the experiments. |
| Software Dependencies | Yes | One strategy to solve (3) is by linear relaxations and then using off-the-shelf MILP solvers such as MOSEK (Ap S, 2019) or GUROBI (Gurobi Optimization, LLC, 2023). |
| Experiment Setup | Yes | Regarding hyperparameter settings, we set the number of explanatory nodes M and components m according to the ground truth explanations for all the baselines if they are available. ... The number of permutations used to compute the Myerson-Taylor index is set to 200, and we use MOSEK (Ap S, 2019) with default parameters for the motif search. |