Explaining the Explainers in Graph Neural Networks: a Comparative Study

Explaining the Explainers in Graph Neural Networks: a Comparative Study

27 October 2022

Andrea Passerini

Papers citing "Explaining the Explainers in Graph Neural Networks: a Comparative Study"

15 / 15 papers shown

Title
Interpretable High-order Knowledge Graph Neural Network for Predicting Synthetic Lethality in Human Cancers Xuexin Chen Ruichu Cai Zhengting Huang Zijian Li Jie Zheng Min Wu 36 0 0 08 Mar 2025
GIN-Graph: A Generative Interpretation Network for Model-Level Explanation of Graph Neural Networks Xiao Yue Guangzhi Qu Lige Gan GAN FAtt AI4CE 58 0 0 08 Mar 2025
CAGN-GAT Fusion: A Hybrid Contrastive Attentive Graph Neural Network for Network Intrusion Detection Md Abrar Jahin S. M. Mridha Raihan Kabir Md. Rashedul Islam Yutaka Watanobe Hezerul Abdul Karim 41 0 0 02 Mar 2025
GraphXAIN: Narratives to Explain Graph Neural Networks Mateusz Cedro David Martens 39 0 0 04 Nov 2024
Logical Distillation of Graph Neural Networks Alexander Pluska Pascal Welke Thomas Gärtner Sagar Malhotra 23 0 0 11 Jun 2024
Globally Interpretable Graph Learning via Distribution Matching Yi Nian Yurui Chang Wei Jin Lu Lin OOD 50 4 0 18 Jun 2023
Hierarchical Graph Transformer with Adaptive Node Sampling Zaixin Zhang Qi Liu Qingyong Hu Cheekong Lee 65 82 0 08 Oct 2022
BAGEL: A Benchmark for Assessing Graph Neural Network Explanations Mandeep Rathee Thorben Funke Avishek Anand Megha Khosla 20 14 0 28 Jun 2022
Equivariant Mesh Attention Networks Sourya Basu Jose Gallego-Posada Francesco Vigano J. Rowbottom Taco S. Cohen 3DPC MDE AI4CE 33 10 0 21 May 2022
Approximately Equivariant Networks for Imperfectly Symmetric Dynamics Rui Wang Robin G. Walters Rose Yu 25 73 0 28 Jan 2022
A Survey of Visual Transformers Yang Liu Yao Zhang Yixin Wang Feng Hou Jin Yuan Jiang Tian Yang Zhang Zhongchao Shi Jianping Fan Zhiqiang He 3DGS ViT 58 325 0 11 Nov 2021
Frame Averaging for Invariant and Equivariant Network Design Omri Puny Matan Atzmon Heli Ben-Hamu Ishan Misra Aditya Grover Edward James Smith Y. Lipman FedML 33 90 0 07 Oct 2021
A Meta-Learning Approach for Training Explainable Graph Neural Networks Indro Spinelli Simone Scardapane A. Uncini 29 19 0 20 Sep 2021
CF-GNNExplainer: Counterfactual Explanations for Graph Neural Networks Ana Lucic Maartje ter Hoeve Gabriele Tolomei Maarten de Rijke Fabrizio Silvestri 107 87 0 05 Feb 2021
Explainability in Graph Neural Networks: A Taxonomic Survey Hao Yuan Haiyang Yu Shurui Gui Shuiwang Ji 159 463 0 31 Dec 2020