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ProtGNN: Towards Self-Explaining Graph Neural Networks

ProtGNN: Towards Self-Explaining Graph Neural Networks

2 December 2021
Zaixin Zhang
Qi Liu
Hao Wang
Chengqiang Lu
Chee-Kong Lee
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Papers citing "ProtGNN: Towards Self-Explaining Graph Neural Networks"

27 / 27 papers shown
Title
Framework GNN-AID: Graph Neural Network Analysis Interpretation and Defense
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
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
48
0
0
08 Mar 2025
Recent Advances in Malware Detection: Graph Learning and Explainability
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
This looks like what? Challenges and Future Research Directions for Part-Prototype Models
This looks like what? Challenges and Future Research Directions for Part-Prototype Models
Khawla Elhadri
Tomasz Michalski
Adam Wróbel
Jorg Schlotterer
Bartosz Zieliñski
C. Seifert
88
0
0
13 Feb 2025
Graph Dimension Attention Networks for Enterprise Credit Assessment
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
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
43
36
0
07 Mar 2024
A differentiable Gaussian Prototype Layer for explainable Segmentation
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
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
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
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
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
Combining Stochastic Explainers and Subgraph Neural Networks can Increase Expressivity and Interpretability
Indro Spinelli
Michele Guerra
F. Bianchi
Simone Scardapane
38
0
0
14 Apr 2023
An Equivariant Generative Framework for Molecular Graph-Structure
  Co-Design
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
ICICLE: Interpretable Class Incremental Continual Learning
Dawid Rymarczyk
Joost van de Weijer
Bartosz Zieliñski
Bartlomiej Twardowski
CLL
34
28
0
14 Mar 2023
Unnoticeable Backdoor Attacks on Graph Neural Networks
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
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
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
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
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
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
L2XGNN: Learning to Explain Graph Neural Networks
G. Serra
Mathias Niepert
40
7
0
28 Sep 2022
Model Inversion Attacks against Graph Neural Networks
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
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
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
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
Explainability in Graph Neural Networks: A Taxonomic Survey
Hao Yuan
Haiyang Yu
Shurui Gui
Shuiwang Ji
167
596
0
31 Dec 2020
MoleculeNet: A Benchmark for Molecular Machine Learning
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
260
1,789
0
02 Mar 2017
1