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PAGE: Parametric Generative Explainer for Graph Neural Network

PAGE: Parametric Generative Explainer for Graph Neural Network

26 August 2024
Yang Qiu
Wei Liu
Jun Wang
Ruixuan Li
    BDL
ArXivPDFHTML

Papers citing "PAGE: Parametric Generative Explainer for Graph Neural Network"

14 / 14 papers shown
Title
Global Explainability of GNNs via Logic Combination of Learned Concepts
Global Explainability of GNNs via Logic Combination of Learned Concepts
Steve Azzolin
Antonio Longa
Pietro Barbiero
Pietro Lio
Andrea Passerini
47
55
0
13 Oct 2022
Reinforced Causal Explainer for Graph Neural Networks
Reinforced Causal Explainer for Graph Neural Networks
Xiang Wang
Y. Wu
An Zhang
Fuli Feng
Xiangnan He
Tat-Seng Chua
CML
101
48
0
23 Apr 2022
Explainability in Graph Neural Networks: An Experimental Survey
Explainability in Graph Neural Networks: An Experimental Survey
Peibo Li
Yixing Yang
Maurice Pagnucco
Yang Song
46
31
0
17 Mar 2022
GraphSVX: Shapley Value Explanations for Graph Neural Networks
GraphSVX: Shapley Value Explanations for Graph Neural Networks
Alexandre Duval
Fragkiskos D. Malliaros
FAtt
54
89
0
18 Apr 2021
Generative Causal Explanations for Graph Neural Networks
Generative Causal Explanations for Graph Neural Networks
Wanyu Lin
Hao Lan
Baochun Li
CML
59
175
0
14 Apr 2021
On Explainability of Graph Neural Networks via Subgraph Explorations
On Explainability of Graph Neural Networks via Subgraph Explorations
Hao Yuan
Haiyang Yu
Jie Wang
Kang Li
Shuiwang Ji
FAtt
78
389
0
09 Feb 2021
XGNN: Towards Model-Level Explanations of Graph Neural Networks
XGNN: Towards Model-Level Explanations of Graph Neural Networks
Haonan Yuan
Jiliang Tang
Xia Hu
Shuiwang Ji
73
398
0
03 Jun 2020
GraphLIME: Local Interpretable Model Explanations for Graph Neural
  Networks
GraphLIME: Local Interpretable Model Explanations for Graph Neural Networks
Q. Huang
M. Yamada
Yuan Tian
Dinesh Singh
Dawei Yin
Yi-Ju Chang
FAtt
72
352
0
17 Jan 2020
Explainability Techniques for Graph Convolutional Networks
Explainability Techniques for Graph Convolutional Networks
Federico Baldassarre
Hossein Azizpour
GNN
FAtt
161
268
0
31 May 2019
A Comprehensive Survey on Graph Neural Networks
A Comprehensive Survey on Graph Neural Networks
Zonghan Wu
Shirui Pan
Fengwen Chen
Guodong Long
Chengqi Zhang
Philip S. Yu
FaML
GNN
AI4TS
AI4CE
672
8,496
0
03 Jan 2019
Graph Neural Networks: A Review of Methods and Applications
Graph Neural Networks: A Review of Methods and Applications
Jie Zhou
Ganqu Cui
Shengding Hu
Zhengyan Zhang
Cheng Yang
Zhiyuan Liu
Lifeng Wang
Changcheng Li
Maosong Sun
AI4CE
GNN
995
5,493
0
20 Dec 2018
How Powerful are Graph Neural Networks?
How Powerful are Graph Neural Networks?
Keyulu Xu
Weihua Hu
J. Leskovec
Stefanie Jegelka
GNN
224
7,623
0
01 Oct 2018
Semi-Supervised Classification with Graph Convolutional Networks
Semi-Supervised Classification with Graph Convolutional Networks
Thomas Kipf
Max Welling
GNN
SSL
587
28,999
0
09 Sep 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
Marco Tulio Ribeiro
Sameer Singh
Carlos Guestrin
FAtt
FaML
1.1K
16,931
0
16 Feb 2016
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