ProtGNN: Towards Self-Explaining Graph Neural Networks

2 December 2021

Qi Liu

Papers citing "ProtGNN: Towards Self-Explaining Graph Neural Networks"

26 / 26 papers shown

Title
Framework GNN-AID: Graph Neural Network Analysis Interpretation and Defense Kirill Lukyanov Mikhail Drobyshevskiy Georgii Sazonov Mikhail Soloviov Ilya Makarov GNN 56 0 0 06 May 2025
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 46 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
Graph Dimension Attention Networks for Enterprise Credit Assessment Shaopeng Wei Béni Egressy Xingyan Chen Yu Zhao Fuzhen Zhuang Roger Wattenhofer Gang Kou 42 0 0 16 Jul 2024
A Survey of Graph Neural Networks in Real world: Imbalance, Noise, Privacy and OOD Challenges Wei Ju Siyu Yi Yifan Wang Zhiping Xiao Zhengyan Mao ... Senzhang Wang Xinwang Liu Xiao Luo Philip S. Yu Ming Zhang AI4CE 41 36 0 07 Mar 2024
A differentiable Gaussian Prototype Layer for explainable Segmentation M. Gerstenberger Steffen Maass Peter Eisert S. Bosse 35 4 0 25 Jun 2023
Quantifying the Intrinsic Usefulness of Attributional Explanations for Graph Neural Networks with Artificial Simulatability Studies Jonas Teufel Luca Torresi Pascal Friederich FAtt 34 1 0 25 May 2023
Robust Ante-hoc Graph Explainer using Bilevel Optimization Kha-Dinh Luong Mert Kosan A. Silva Ambuj K. Singh 41 6 0 25 May 2023
Learning Subpocket Prototypes for Generalizable Structure-based Drug Design Zaixin Zhang Qi Liu 40 34 0 22 May 2023
Self-Explainable Graph Neural Networks for Link Prediction Huaisheng Zhu Dongsheng Luo Xianfeng Tang Junjie Xu Hui Liu Suhang Wang 23 1 0 21 May 2023
Combining Stochastic Explainers and Subgraph Neural Networks can Increase Expressivity and Interpretability Indro Spinelli Michele Guerra F. Bianchi Simone Scardapane 36 0 0 14 Apr 2023
An Equivariant Generative Framework for Molecular Graph-Structure Co-Design Zaixin Zhang Qi Liu Cheekong Lee Chang-Yu Hsieh Enhong Chen 29 18 0 12 Apr 2023
ICICLE: Interpretable Class Incremental Continual Learning Dawid Rymarczyk Joost van de Weijer Bartosz Zieliñski Bartlomiej Twardowski CLL 32 28 0 14 Mar 2023
Unnoticeable Backdoor Attacks on Graph Neural Networks Enyan Dai Minhua Lin Xiang Zhang Suhang Wang AAML 29 47 0 11 Feb 2023
ProtoSeg: Interpretable Semantic Segmentation with Prototypical Parts Mikolaj Sacha Dawid Rymarczyk Lukasz Struski Jacek Tabor Bartosz Zieliñski VLM 38 29 0 28 Jan 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
A Comprehensive Survey on Enterprise Financial Risk Analysis from Big Data Perspective Yu Zhao Huaming Du Qing Li Fuzhen Zhuang Ji Liu Gang Kou Gang Kou 30 1 0 28 Nov 2022
MEGAN: Multi-Explanation Graph Attention Network Jonas Teufel Luca Torresi Patrick Reiser Pascal Friederich 26 8 0 23 Nov 2022
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
Model Inversion Attacks against Graph Neural Networks Zaixin Zhang Qi Liu Zhenya Huang Hao Wang Cheekong Lee Enhong AAML 28 35 0 16 Sep 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
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: A Taxonomic Survey Hao Yuan Haiyang Yu Shurui Gui Shuiwang Ji 167 595 0 31 Dec 2020
MoleculeNet: A Benchmark for Molecular Machine Learning Zhenqin Wu Bharath Ramsundar Evan N. Feinberg Joseph Gomes C. Geniesse Aneesh S. Pappu K. Leswing Vijay S. Pande OOD 251 1,787 0 02 Mar 2017