Explainability Techniques for Graph Convolutional Networks

31 May 2019

Papers citing "Explainability Techniques for Graph Convolutional Networks"

50 / 62 papers shown

Title
Interpretability of Graph Neural Networks to Assess Effects of Global Change Drivers on Ecological Networks Emré Anakok Pierre Barbillon Colin Fontaine Elisa Thébault 57 0 0 19 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 65 0 0 08 Mar 2025
Recent Advances in Malware Detection: Graph Learning and Explainability Hossein Shokouhinejad Roozbeh Razavi-Far Hesamodin Mohammadian Mahdi Rabbani Samuel Ansong Griffin Higgins Ali Ghorbani AAML 78 2 0 14 Feb 2025
On the Probability of Necessity and Sufficiency of Explaining Graph Neural Networks: A Lower Bound Optimization Approach Ruichu Cai Yuxuan Zhu Xuexin Chen Yuan Fang Min-man Wu Jie Qiao Zhifeng Hao 54 7 0 31 Dec 2024
Explainable Graph Neural Networks Under Fire Zhong Li Simon Geisler Yuhang Wang Stephan Günnemann M. Leeuwen AAML 43 0 0 10 Jun 2024
MAGE: Model-Level Graph Neural Networks Explanations via Motif-based Graph Generation Zhaoning Yu Hongyang Gao 52 3 0 21 May 2024
Incorporating Retrieval-based Causal Learning with Information Bottlenecks for Interpretable Graph Neural Networks Jiahua Rao Jiancong Xie Hanjing Lin Shuangjia Zheng Zhen Wang Yuedong Yang 23 0 0 07 Feb 2024
Towards Fine-Grained Explainability for Heterogeneous Graph Neural Network Tong Li Jiale Deng Yanyan Shen Luyu Qiu Hu Yongxiang Caleb Chen Cao 25 5 0 23 Dec 2023
D4Explainer: In-Distribution GNN Explanations via Discrete Denoising Diffusion Jialin Chen Shirley Wu Abhijit Gupta Rex Ying DiffM 42 5 0 30 Oct 2023
Robust Ranking Explanations Chao Chen Chenghua Guo Guixiang Ma Ming Zeng Xi Zhang Sihong Xie FAtt AAML 37 0 0 08 Jul 2023
DEGREE: Decomposition Based Explanation For Graph Neural Networks Qizhang Feng Ninghao Liu Fan Yang Ruixiang Tang Mengnan Du Xia Hu 30 22 0 22 May 2023
Dynamic Causal Explanation Based Diffusion-Variational Graph Neural Network for Spatio-temporal Forecasting G. Liang Prayag Tiwari Sławomir Nowaczyk Stefan Byttner F. Alonso-Fernandez DiffM 44 13 0 16 May 2023
Unstructured and structured data: Can we have the best of both worlds with large language models? W. Tan 34 1 0 25 Apr 2023
CI-GNN: A Granger Causality-Inspired Graph Neural Network for Interpretable Brain Network-Based Psychiatric Diagnosis Kaizhong Zheng Shujian Yu Badong Chen CML 48 32 0 04 Jan 2023
Towards Prototype-Based Self-Explainable Graph Neural Network Enyan Dai Suhang Wang 33 12 0 05 Oct 2022
L2XGNN: Learning to Explain Graph Neural Networks G. Serra Mathias Niepert 40 7 0 28 Sep 2022
Evaluating Explainability for Graph Neural Networks Chirag Agarwal Owen Queen Himabindu Lakkaraju Marinka Zitnik 51 102 0 19 Aug 2022
A Survey of Explainable Graph Neural Networks: Taxonomy and Evaluation Metrics Yiqiao Li Jianlong Zhou Sunny Verma Fang Chen XAI 50 39 0 26 Jul 2022
A Survey on Hyperlink Prediction Cang Chen Yang-Yu Liu 3DV AI4CE 17 40 0 06 Jul 2022
Towards Faithful and Consistent Explanations for Graph Neural Networks Tianxiang Zhao Dongsheng Luo Xiang Zhang Suhang Wang FAtt 65 19 0 27 May 2022
DT+GNN: A Fully Explainable Graph Neural Network using Decision Trees Peter Müller Lukas Faber Karolis Martinkus Roger Wattenhofer 43 8 0 26 May 2022
A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection Bingzhe Wu Jintang Li Junchi Yu Yatao Bian Hengtong Zhang ... Guangyu Sun Peng Cui Zibin Zheng Zhe Liu P. Zhao OOD 45 25 0 20 May 2022
Trustworthy Graph Neural Networks: Aspects, Methods and Trends He Zhang Bang Wu Xingliang Yuan Shirui Pan Hanghang Tong Jian Pei 45 104 0 16 May 2022
Explainability in Graph Neural Networks: An Experimental Survey Peibo Li Yixing Yang Maurice Pagnucco Yang Song 29 31 0 17 Mar 2022
An explainability framework for cortical surface-based deep learning Fernanda L. Ribeiro S. Bollmann R. Cunnington A. M. Puckett FAtt AAML MedIm 24 2 0 15 Mar 2022
Differentially Private Graph Classification with GNNs Tamara T. Mueller Johannes C. Paetzold Chinmay Prabhakar Dmitrii Usynin Daniel Rueckert Georgios Kaissis 52 18 0 05 Feb 2022
MotifExplainer: a Motif-based Graph Neural Network Explainer Zhaoning Yu Hongyang Gao 44 15 0 01 Feb 2022
Interpretable and Generalizable Graph Learning via Stochastic Attention Mechanism Siqi Miao Miaoyuan Liu Pan Li 18 197 0 31 Jan 2022
GStarX: Explaining Graph Neural Networks with Structure-Aware Cooperative Games Shichang Zhang Yozen Liu Neil Shah Yizhou Sun FAtt 33 45 0 28 Jan 2022
Deconfounding to Explanation Evaluation in Graph Neural Networks Yingmin Wu Xiang Wang An Zhang Xia Hu Fuli Feng Xiangnan He Tat-Seng Chua FAtt CML 17 14 0 21 Jan 2022
A Cognitive Explainer for Fetal ultrasound images classifier Based on Medical Concepts Ying-Shuai Wanga Yunxia Liua Licong Dongc Xuzhou Wua Huabin Zhangb Qiongyu Yed Desheng Sunc Xiaobo Zhoue Kehong Yuan 27 0 0 19 Jan 2022
Self-learn to Explain Siamese Networks Robustly Chao Chen Yifan Shen Guixiang Ma Xiangnan Kong S. Rangarajan Xi Zhang Sihong Xie 48 5 0 15 Sep 2021
GCExplainer: Human-in-the-Loop Concept-based Explanations for Graph Neural Networks Lucie Charlotte Magister Dmitry Kazhdan Vikash Singh Pietro Lio 35 48 0 25 Jul 2021
Bridging the Gap between Spatial and Spectral Domains: A Unified Framework for Graph Neural Networks Zhiqian Chen Fanglan Chen Lei Zhang Taoran Ji Kaiqun Fu Liang Zhao Feng Chen Lingfei Wu Charu C. Aggarwal Chang-Tien Lu 53 18 0 21 Jul 2021
A Survey on Graph-Based Deep Learning for Computational Histopathology David Ahmedt-Aristizabal M. Armin Simon Denman Clinton Fookes L. Petersson GNN AI4CE 26 108 0 01 Jul 2021
Probing GNN Explainers: A Rigorous Theoretical and Empirical Analysis of GNN Explanation Methods Chirag Agarwal Marinka Zitnik Himabindu Lakkaraju 27 51 0 16 Jun 2021
Improving Molecular Graph Neural Network Explainability with Orthonormalization and Induced Sparsity Ryan Henderson Djork-Arné Clevert F. Montanari 33 26 0 11 May 2021
GraphSVX: Shapley Value Explanations for Graph Neural Networks Alexandre Duval Fragkiskos D. Malliaros FAtt 17 86 0 18 Apr 2021
MEG: Generating Molecular Counterfactual Explanations for Deep Graph Networks Danilo Numeroso D. Bacciu 29 38 0 16 Apr 2021
Sampling methods for efficient training of graph convolutional networks: A survey Xin Liu Yurui Lai Lei Deng Guoqi Li Xiaochun Ye Xiaochun Ye GNN 29 100 0 10 Mar 2021
Graph Computing for Financial Crime and Fraud Detection: Trends, Challenges and Outlook Eren Kurshan Hongda Shen GNN 37 32 0 02 Mar 2021
Financial Crime & Fraud Detection Using Graph Computing: Application Considerations & Outlook Eren Kurshan Honda Shen Haojie Yu GNN FaML 40 26 0 02 Mar 2021
Graph Neural Networks: Taxonomy, Advances and Trends Yu Zhou Haixia Zheng Xin Huang Shufeng Hao Dengao Li Jumin Zhao AI4TS 27 117 0 16 Dec 2020
Explanation from Specification Harish Naik Gyorgy Turán XAI 27 0 0 13 Dec 2020
NCGNN: Node-Level Capsule Graph Neural Network for Semisupervised Classification Rui Yang Wenrui Dai Chenglin Li Junni Zou H. Xiong 34 20 0 07 Dec 2020
Quantifying Explainers of Graph Neural Networks in Computational Pathology Guillaume Jaume Pushpak Pati Behzad Bozorgtabar Antonio Foncubierta-Rodríguez Florinda Feroce A. Anniciello T. Rau Jean-Philippe Thiran M. Gabrani O. Goksel FAtt 26 76 0 25 Nov 2020
xFraud: Explainable Fraud Transaction Detection Susie Xi Rao Shuai Zhang Zhichao Han Zitao Zhang Wei Min Zhiyao Chen Yinan Shan Yang Zhao Ce Zhang 33 49 0 24 Nov 2020
Graph Neural Networks in Recommender Systems: A Survey Shiwen Wu Fei Sun Wentao Zhang Xu Xie Bin Cui GNN 60 1,179 0 04 Nov 2020
Contrastive Graph Neural Network Explanation Lukas Faber A. K. Moghaddam Roger Wattenhofer 31 36 0 26 Oct 2020
Interpreting Graph Neural Networks for NLP With Differentiable Edge Masking M. Schlichtkrull Nicola De Cao Ivan Titov AI4CE 36 214 0 01 Oct 2020