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Parameterized Explainer for Graph Neural Network

Parameterized Explainer for Graph Neural Network

9 November 2020
Dongsheng Luo
Wei Cheng
Dongkuan Xu
Wenchao Yu
Bo Zong
Haifeng Chen
Xiang Zhang
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Papers citing "Parameterized Explainer for Graph Neural Network"

50 / 288 papers shown
Title
How Interpretable Are Interpretable Graph Neural Networks?
How Interpretable Are Interpretable Graph Neural Networks?
Yongqiang Chen
Yatao Bian
Bo Han
James Cheng
42
4
0
12 Jun 2024
Explainable Graph Neural Networks Under Fire
Explainable Graph Neural Networks Under Fire
Zhong Li
Simon Geisler
Yuhang Wang
Stephan Günnemann
M. Leeuwen
AAML
36
0
0
10 Jun 2024
Explainable AI for Mental Disorder Detection via Social Media: A survey
  and outlook
Explainable AI for Mental Disorder Detection via Social Media: A survey and outlook
Yusif Ibrahimov
Tarique Anwar
Tommy Yuan
31
3
0
10 Jun 2024
Enhancing Size Generalization in Graph Neural Networks through
  Disentangled Representation Learning
Enhancing Size Generalization in Graph Neural Networks through Disentangled Representation Learning
Zheng Huang
Qihui Yang
Dawei Zhou
Yujun Yan
AI4CE
28
2
0
07 Jun 2024
GNNAnatomy: Systematic Generation and Evaluation of Multi-Level
  Explanations for Graph Neural Networks
GNNAnatomy: Systematic Generation and Evaluation of Multi-Level Explanations for Graph Neural Networks
Hsiao-Ying Lu
Yiran Li
Ujwal Pratap Krishna Kaluvakolanu Thyagarajan
Kwan-Liu Ma
32
1
0
06 Jun 2024
The Intelligible and Effective Graph Neural Additive Networks
The Intelligible and Effective Graph Neural Additive Networks
Maya Bechler-Speicher
Amir Globerson
Ran Gilad-Bachrach
31
5
0
03 Jun 2024
SIG: Efficient Self-Interpretable Graph Neural Network for
  Continuous-time Dynamic Graphs
SIG: Efficient Self-Interpretable Graph Neural Network for Continuous-time Dynamic Graphs
Lanting Fang
Yulian Yang
Kai Wang
Shanshan Feng
Kaiyu Feng
Jie Gui
Shuliang Wang
Y. Ong
32
1
0
29 May 2024
Explainable Molecular Property Prediction: Aligning Chemical Concepts
  with Predictions via Language Models
Explainable Molecular Property Prediction: Aligning Chemical Concepts with Predictions via Language Models
Zhenzhong Wang
Zehui Lin
Wanyu Lin
Ming Yang
Minggang Zeng
Kay Chen Tan
21
3
0
25 May 2024
Explaining Graph Neural Networks via Structure-aware Interaction Index
Explaining Graph Neural Networks via Structure-aware Interaction Index
Ngoc H. Bui
Hieu Trung Nguyen
Viet Anh Nguyen
Rex Ying
FAtt
38
4
0
23 May 2024
Utilizing Description Logics for Global Explanations of Heterogeneous
  Graph Neural Networks
Utilizing Description Logics for Global Explanations of Heterogeneous Graph Neural Networks
Dominik Köhler
Stefan Heindorf
26
0
0
21 May 2024
MAGE: Model-Level Graph Neural Networks Explanations via Motif-based Graph Generation
MAGE: Model-Level Graph Neural Networks Explanations via Motif-based Graph Generation
Zhaoning Yu
Hongyang Gao
37
3
0
21 May 2024
TimeX++: Learning Time-Series Explanations with Information Bottleneck
TimeX++: Learning Time-Series Explanations with Information Bottleneck
Zichuan Liu
Tianchun Wang
Jimeng Shi
Xu Zheng
Zhuomin Chen
Lei Song
Wenqian Dong
J. Obeysekera
Farhad Shirani
Dongsheng Luo
AI4TS
24
7
0
15 May 2024
Predictive Modeling with Temporal Graphical Representation on Electronic
  Health Records
Predictive Modeling with Temporal Graphical Representation on Electronic Health Records
Jiayuan Chen
Changchang Yin
Yuanlong Wang
Ping Zhang
30
2
0
07 May 2024
EiG-Search: Generating Edge-Induced Subgraphs for GNN Explanation in
  Linear Time
EiG-Search: Generating Edge-Induced Subgraphs for GNN Explanation in Linear Time
Shengyao Lu
Bang Liu
Keith G. Mills
Jiao He
Di Niu
39
3
0
02 May 2024
Generating Robust Counterfactual Witnesses for Graph Neural Networks
Generating Robust Counterfactual Witnesses for Graph Neural Networks
Dazhuo Qiu
Mengying Wang
Arijit Khan
Yinghui Wu
27
2
0
30 Apr 2024
Graph Machine Learning in the Era of Large Language Models (LLMs)
Graph Machine Learning in the Era of Large Language Models (LLMs)
Wenqi Fan
Shijie Wang
Jiani Huang
Zhikai Chen
Yu Song
...
Haitao Mao
Hui Liu
Xiaorui Liu
Dawei Yin
Qing Li
AI4CE
26
23
0
23 Apr 2024
Improving the interpretability of GNN predictions through
  conformal-based graph sparsification
Improving the interpretability of GNN predictions through conformal-based graph sparsification
Pablo Sánchez-Martín
Kinaan Aamir Khan
Isabel Valera
29
3
0
18 Apr 2024
Comprehensible Artificial Intelligence on Knowledge Graphs: A survey
Comprehensible Artificial Intelligence on Knowledge Graphs: A survey
Simon Schramm
C. Wehner
Ute Schmid
25
25
0
04 Apr 2024
GreeDy and CoDy: Counterfactual Explainers for Dynamic Graphs
GreeDy and CoDy: Counterfactual Explainers for Dynamic Graphs
Zhan Qu
Daniel Gomm
Michael Färber
CML
FAtt
36
1
0
25 Mar 2024
MaliGNNoma: GNN-Based Malicious Circuit Classifier for Secure Cloud
  FPGAs
MaliGNNoma: GNN-Based Malicious Circuit Classifier for Secure Cloud FPGAs
Lilas Alrahis
Hassan Nassar
Jonas Krautter
Dennis R. E. Gnad
Lars Bauer
Jörg Henkel
M. Tahoori
27
2
0
04 Mar 2024
Position: Topological Deep Learning is the New Frontier for Relational
  Learning
Position: Topological Deep Learning is the New Frontier for Relational Learning
Theodore Papamarkou
Tolga Birdal
Michael M. Bronstein
Gunnar Carlsson
Justin Curry
...
Petar Velickovic
Bei Wang
Yusu Wang
Guo-Wei Wei
Ghada Zamzmi
AI4CE
54
25
0
14 Feb 2024
Feature Attribution with Necessity and Sufficiency via Dual-stage
  Perturbation Test for Causal Explanation
Feature Attribution with Necessity and Sufficiency via Dual-stage Perturbation Test for Causal Explanation
Xuexin Chen
Ruichu Cai
Zhengting Huang
Yuxuan Zhu
Julien Horwood
Zhifeng Hao
Zijian Li
Jose Miguel Hernandez-Lobato
AAML
36
2
0
13 Feb 2024
PAC Learnability under Explanation-Preserving Graph Perturbations
PAC Learnability under Explanation-Preserving Graph Perturbations
Xu Zheng
Farhad Shirani
Tianchun Wang
Shouwei Gao
Wenqian Dong
Wei Cheng
Dongsheng Luo
22
0
0
07 Feb 2024
Incorporating Retrieval-based Causal Learning with Information
  Bottlenecks for Interpretable Graph Neural Networks
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
19
0
0
07 Feb 2024
LIPSTICK: Corruptibility-Aware and Explainable Graph Neural
  Network-based Oracle-Less Attack on Logic Locking
LIPSTICK: Corruptibility-Aware and Explainable Graph Neural Network-based Oracle-Less Attack on Logic Locking
Yeganeh Aghamohammadi
Amin Rezaei
AAML
13
3
0
06 Feb 2024
MolTC: Towards Molecular Relational Modeling In Language Models
MolTC: Towards Molecular Relational Modeling In Language Models
Junfeng Fang
Shuai Zhang
Chang Wu
Zhengyi Yang
Zhiyuan Liu
Sihang Li
Kun Wang
Wenjie Du
Xiang Wang
27
19
0
06 Feb 2024
PowerGraph: A power grid benchmark dataset for graph neural networks
PowerGraph: A power grid benchmark dataset for graph neural networks
Anna Varbella
Kenza Amara
B. Gjorgiev
Mennatallah El-Assady
G. Sansavini
18
5
0
05 Feb 2024
EXGC: Bridging Efficiency and Explainability in Graph Condensation
EXGC: Bridging Efficiency and Explainability in Graph Condensation
Junfeng Fang
Xinglin Li
Yongduo Sui
Yuan Gao
Guibin Zhang
Kun Wang
Xiang Wang
Xiangnan He
DD
51
19
0
05 Feb 2024
Generating In-Distribution Proxy Graphs for Explaining Graph Neural
  Networks
Generating In-Distribution Proxy Graphs for Explaining Graph Neural Networks
Zhuomin Chen
Jiaxing Zhang
Jingchao Ni
Xiaoting Li
Yuchen Bian
Md. Mezbahul Islam
A. Mondal
Hua Wei
Dongsheng Luo
16
1
0
03 Feb 2024
X-CBA: Explainability Aided CatBoosted Anomal-E for Intrusion Detection
  System
X-CBA: Explainability Aided CatBoosted Anomal-E for Intrusion Detection System
Kıymet Kaya
Elif Ak
Sumeyye Bas
B. Canberk
Ş. Öğüdücü
AAML
26
1
0
01 Feb 2024
GOAt: Explaining Graph Neural Networks via Graph Output Attribution
GOAt: Explaining Graph Neural Networks via Graph Output Attribution
Shengyao Lu
Keith G. Mills
Jiao He
Bang Liu
Di Niu
FAtt
29
8
0
26 Jan 2024
SynHING: Synthetic Heterogeneous Information Network Generation for
  Graph Learning and Explanation
SynHING: Synthetic Heterogeneous Information Network Generation for Graph Learning and Explanation
Ming-Yi Hong
Yi-Hsiang Huang
Shao-En Lin
You-Chen Teng
Chih-Yu Wang
Che Lin
33
0
0
07 Jan 2024
Beyond Fidelity: Explaining Vulnerability Localization of Learning-based
  Detectors
Beyond Fidelity: Explaining Vulnerability Localization of Learning-based Detectors
Baijun Cheng
Shengming Zhao
Kailong Wang
Meizhen Wang
Guangdong Bai
Ruitao Feng
Yao Guo
Lei Ma
Haoyu Wang
FAtt
AAML
29
7
0
05 Jan 2024
View-based Explanations for Graph Neural Networks
View-based Explanations for Graph Neural Networks
Tingyang Chen
Dazhuo Qiu
Yinghui Wu
Arijit Khan
Xiangyu Ke
Yunjun Gao
33
9
0
04 Jan 2024
On Discprecncies between Perturbation Evaluations of Graph Neural
  Network Attributions
On Discprecncies between Perturbation Evaluations of Graph Neural Network Attributions
Razieh Rezaei
Alireza Dizaji
Ashkan Khakzar
Anees Kazi
Nassir Navab
Daniel Rueckert
13
0
0
01 Jan 2024
Explainability-Based Adversarial Attack on Graphs Through Edge
  Perturbation
Explainability-Based Adversarial Attack on Graphs Through Edge Perturbation
Dibaloke Chanda
Saba Heidari Gheshlaghi
Nasim Yahya Soltani
AAML
15
0
0
28 Dec 2023
Towards Fine-Grained Explainability for Heterogeneous Graph Neural
  Network
Towards Fine-Grained Explainability for Heterogeneous Graph Neural Network
Tong Li
Jiale Deng
Yanyan Shen
Luyu Qiu
Hu Yongxiang
Caleb Chen Cao
23
5
0
23 Dec 2023
Towards Human-like Perception: Learning Structural Causal Model in
  Heterogeneous Graph
Towards Human-like Perception: Learning Structural Causal Model in Heterogeneous Graph
Tianqianjin Lin
Kaisong Song
Zhuoren Jiang
Yangyang Kang
Weikang Yuan
Xurui Li
Changlong Sun
Cui Huang
Xiaozhong Liu
28
6
0
10 Dec 2023
Factorized Explainer for Graph Neural Networks
Factorized Explainer for Graph Neural Networks
Rundong Huang
Farhad Shirani
Dongsheng Luo
37
8
0
09 Dec 2023
Predicting and Interpreting Energy Barriers of Metallic Glasses with
  Graph Neural Networks
Predicting and Interpreting Energy Barriers of Metallic Glasses with Graph Neural Networks
Haoyu Li
Shichang Zhang
Longwen Tang
Mathieu Bauchy
Yizhou Sun
AI4CE
40
1
0
08 Dec 2023
Enhancing the Rationale-Input Alignment for Self-explaining
  Rationalization
Enhancing the Rationale-Input Alignment for Self-explaining Rationalization
Wei Liu
Haozhao Wang
Jun Wang
Zhiying Deng
Yuankai Zhang
Chengwei Wang
Ruixuan Li
30
9
0
07 Dec 2023
Everybody Needs a Little HELP: Explaining Graphs via Hierarchical
  Concepts
Everybody Needs a Little HELP: Explaining Graphs via Hierarchical Concepts
Jonas Jürß
Lucie Charlotte Magister
Pietro Barbiero
Pietro Lió
Nikola Simidjievski
28
1
0
25 Nov 2023
Exploring Causal Learning through Graph Neural Networks: An In-depth
  Review
Exploring Causal Learning through Graph Neural Networks: An In-depth Review
Simi Job
Xiaohui Tao
Taotao Cai
Haoran Xie
Lin Li
Jianming Yong
Qing Li
CML
AI4CE
21
5
0
25 Nov 2023
AMES: A Differentiable Embedding Space Selection Framework for Latent
  Graph Inference
AMES: A Differentiable Embedding Space Selection Framework for Latent Graph Inference
Yuan Lu
Haitz Sáez de Ocáriz Borde
Pietro Lio'
16
2
0
20 Nov 2023
Evaluating Neighbor Explainability for Graph Neural Networks
Evaluating Neighbor Explainability for Graph Neural Networks
Oscar Llorente
Rana Fawzy
Jared Keown
Michal Horemuz
Péter Vaderna
Sándor Laki
Roland Kotroczó
Rita Csoma
János Márk Szalai-Gindl
14
0
0
14 Nov 2023
GRAM: An Interpretable Approach for Graph Anomaly Detection using
  Gradient Attention Maps
GRAM: An Interpretable Approach for Graph Anomaly Detection using Gradient Attention Maps
Yifei Yang
Peng Wang
Xiaofan He
Dongmian Zou
14
5
0
10 Nov 2023
Generative Explanations for Graph Neural Network: Methods and
  Evaluations
Generative Explanations for Graph Neural Network: Methods and Evaluations
Jialin Chen
Kenza Amara
Junchi Yu
Rex Ying
37
3
0
09 Nov 2023
Interpretable Prototype-based Graph Information Bottleneck
Interpretable Prototype-based Graph Information Bottleneck
Sangwoo Seo
Sungwon Kim
Chanyoung Park
11
12
0
30 Oct 2023
TempME: Towards the Explainability of Temporal Graph Neural Networks via
  Motif Discovery
TempME: Towards the Explainability of Temporal Graph Neural Networks via Motif Discovery
Jialin Chen
Rex Ying
AI4TS
19
20
0
30 Oct 2023
D4Explainer: In-Distribution GNN Explanations via Discrete Denoising
  Diffusion
D4Explainer: In-Distribution GNN Explanations via Discrete Denoising Diffusion
Jialin Chen
Shirley Wu
Abhijit Gupta
Rex Ying
DiffM
34
4
0
30 Oct 2023
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