Parameterized Explainer for Graph Neural Network

9 November 2020

Dongkuan Xu

Papers citing "Parameterized Explainer for Graph Neural Network"

50 / 290 papers shown

Title
TempME: Towards the Explainability of Temporal Graph Neural Networks via Motif Discovery Jialin Chen Rex Ying AI4TS 27 21 0 30 Oct 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
Does Invariant Graph Learning via Environment Augmentation Learn Invariance? Yongqiang Chen Yatao Bian Kaiwen Zhou Binghui Xie Bo Han James Cheng OOD 36 34 0 29 Oct 2023
How Well Do Feature-Additive Explainers Explain Feature-Additive Predictors? Zachariah Carmichael Walter J. Scheirer FAtt 42 4 0 27 Oct 2023
Explainable Spatio-Temporal Graph Neural Networks Jiabin Tang Lianghao Xia Chao Huang AI4TS 42 17 0 26 Oct 2023
Network Design through Graph Neural Networks: Identifying Challenges and Improving Performance Donald Loveland Rajmonda Caceres 19 0 0 26 Oct 2023
Towards Self-Interpretable Graph-Level Anomaly Detection Yixin Liu Kaize Ding Qinghua Lu Fuyi Li Leo Yu Zhang Shirui Pan 29 49 0 25 Oct 2023
DyExplainer: Explainable Dynamic Graph Neural Networks Tianchun Wang Dongsheng Luo Wei Cheng Haifeng Chen Xiang Zhang 35 3 0 25 Oct 2023
A Causal Disentangled Multi-Granularity Graph Classification Method Yuan Li Li Liu Penggang Chen Youmin Zhang Guoyin Wang 14 1 0 25 Oct 2023
Transitivity Recovering Decompositions: Interpretable and Robust Fine-Grained Relationships Abhra Chaudhuri Massimiliano Mancini Zeynep Akata Anjan Dutta 32 2 0 24 Oct 2023
Atom-Motif Contrastive Transformer for Molecular Property Prediction Wentao Yu Shuo Chen Chen Gong Gang Niu Masashi Sugiyama ViT 45 2 0 11 Oct 2023
Towards Robust Fidelity for Evaluating Explainability of Graph Neural Networks Xu Zheng Farhad Shirani Tianchun Wang Wei Cheng Zhuomin Chen Haifeng Chen Hua Wei Dongsheng Luo 38 11 0 03 Oct 2023
GNNX-BENCH: Unravelling the Utility of Perturbation-based GNN Explainers through In-depth Benchmarking Mert Kosan S. Verma Burouj Armgaan Khushbu Pahwa Ambuj K. Singh Sourav Medya Sayan Ranu 32 13 0 03 Oct 2023
ACGAN-GNNExplainer: Auxiliary Conditional Generative Explainer for Graph Neural Networks Yiqiao Li Jianlong Zhou Yifei Dong Niusha Shafiabady Fang Chen LLMAG 32 4 0 29 Sep 2023
Augment to Interpret: Unsupervised and Inherently Interpretable Graph Embeddings Gregory Scafarto Madalina Ciortan Simon Tihon Quentin Ferre 23 2 0 28 Sep 2023
GInX-Eval: Towards In-Distribution Evaluation of Graph Neural Network Explanations Kenza Amara Mennatallah El-Assady Rex Ying 30 6 0 28 Sep 2023
A Model-Agnostic Graph Neural Network for Integrating Local and Global Information Wenzhuo Zhou Annie Qu Keiland W Cooper Norbert Fortin Babak Shahbaba 42 1 0 23 Sep 2023
D-Separation for Causal Self-Explanation Wei Liu Jun Wang Yining Qi Rui Li Zhiying Deng YuanKai Zhang Yang Qiu 82 14 0 23 Sep 2023
Towards Data-centric Graph Machine Learning: Review and Outlook Xin Zheng Yixin Liu Zhifeng Bao Meng Fang Xia Hu Alan Wee-Chung Liew Shirui Pan GNN AI4CE 34 19 0 20 Sep 2023
Graph Neural Networks Use Graphs When They Shouldn't Maya Bechler-Speicher Ido Amos Ran Gilad-Bachrach Amir Globerson GNN AI4CE 16 15 0 08 Sep 2023
On the Robustness of Post-hoc GNN Explainers to Label Noise Zhiqiang Zhong Yangqianzi Jiang Davide Mottin AAML NoLa 32 3 0 04 Sep 2023
How Faithful are Self-Explainable GNNs? Marc Christiansen Lea Villadsen Zhiqiang Zhong Stefano Teso Davide Mottin 26 3 0 29 Aug 2023
Building explainable graph neural network by sparse learning for the drug-protein binding prediction Yang Wang Zanyu Shi Timothy W. Richardson Kun Huang P. Weerawarna Yijie Wang 23 0 0 27 Aug 2023
i-Align: an interpretable knowledge graph alignment model Bayu Distiawan Trisedya Flora D. Salim Jeffrey Chan Damiano Spina Falk Scholer Mark Sanderson 18 7 0 26 Aug 2023
XGBD: Explanation-Guided Graph Backdoor Detection Zihan Guan Mengnan Du Ninghao Liu AAML 32 9 0 08 Aug 2023
Semantic Interpretation and Validation of Graph Attention-based Explanations for GNN Models Efimia Panagiotaki D. Martini Lars Kunze 19 4 0 08 Aug 2023
Evaluating Link Prediction Explanations for Graph Neural Networks Claudio Borile Alan Perotti Andre' Panisson FAtt 46 2 0 03 Aug 2023
Counterfactual Graph Transformer for Traffic Flow Prediction Yingbin Yang Kai Du Xingyuan Dai Jianwu Fang AI4TS 35 1 0 01 Aug 2023
Counterfactual Explanations for Graph Classification Through the Lenses of Density Carlo Abrate Giulia Preti Francesco Bonchi 24 1 0 27 Jul 2023
RegExplainer: Generating Explanations for Graph Neural Networks in Regression Task Jiaxing Zhang Zhuomin Chen Hao Mei Dongsheng Luo Hua Wei 45 8 0 15 Jul 2023
MixupExplainer: Generalizing Explanations for Graph Neural Networks with Data Augmentation Jiaxing Zhang Dongsheng Luo Huazhou Wei 25 20 0 15 Jul 2023
Is Task-Agnostic Explainable AI a Myth? Alicja Chaszczewicz 26 2 0 13 Jul 2023
Histopathology Whole Slide Image Analysis with Heterogeneous Graph Representation Learning Tsai Hor Chan Fernando Julio Cendra Lan Ma Guosheng Yin Lequan Yu 34 45 0 09 Jul 2023
A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection Ming Jin Huan Yee Koh Qingsong Wen Daniele Zambon Cesare Alippi G. I. Webb Irwin King Shirui Pan AI4TS AI4CE 44 143 0 07 Jul 2023
ENGAGE: Explanation Guided Data Augmentation for Graph Representation Learning Yucheng Shi Kaixiong Zhou Ninghao Liu 31 11 0 03 Jul 2023
Structure-Sensitive Graph Dictionary Embedding for Graph Classification Guangyi Liu Tong Zhang Xudong Wang Wenting Zhao Chuanwei Zhou Zhen Cui 30 1 0 18 Jun 2023
Advancing Biomedicine with Graph Representation Learning: Recent Progress, Challenges, and Future Directions Fang Li Yi Nian Zenan Sun Cui Tao LM&MA OOD AI4TS AI4CE 33 5 0 18 Jun 2023
Globally Interpretable Graph Learning via Distribution Matching Yi Nian Yurui Chang Wei Jin Lu Lin OOD 58 4 0 18 Jun 2023
On the Interplay of Subset Selection and Informed Graph Neural Networks Niklas Breustedt Paolo Climaco Jochen Garcke J. Hamaekers Gitta Kutyniok D. Lorenz Rick Oerder Chirag Varun Shukla 27 0 0 15 Jun 2023
Efficient GNN Explanation via Learning Removal-based Attribution Yao Rong Guanchu Wang Qizhang Feng Ninghao Liu Zirui Liu Enkelejda Kasneci Xia Hu 28 9 0 09 Jun 2023
Empowering Counterfactual Reasoning over Graph Neural Networks through Inductivity S. Verma Burouj Armgaan Sourav Medya Sayan Ranu CML AI4CE 32 0 0 07 Jun 2023
XInsight: Revealing Model Insights for GNNs with Flow-based Explanations Eli J. Laird Ayesh Madushanka E. Kraka Corey Clark 19 1 0 07 Jun 2023
Message-passing selection: Towards interpretable GNNs for graph classification Wen-Ding Li Kaixuan Chen Shunyu Liu Wenjie Huang Haofei Zhang Yingjie Tian Yun Su Mingli Song 34 1 0 03 Jun 2023
A Survey on Explainability of Graph Neural Networks Jaykumar Kakkad Jaspal Jannu Kartik Sharma Charu C. Aggarwal Sourav Medya 28 24 0 02 Jun 2023
Shift-Robust Molecular Relational Learning with Causal Substructure Namkyeong Lee Kanghoon Yoon Gyoung S. Na Sein Kim Chanyoung Park 26 15 0 29 May 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 36 6 0 25 May 2023
DEGREE: Decomposition Based Explanation For Graph Neural Networks Qizhang Feng Ninghao Liu Fan Yang Ruixiang Tang Mengnan Du Xia Hu 25 22 0 22 May 2023
Self-Explainable Graph Neural Networks for Link Prediction Huaisheng Zhu Dongsheng Luo Xianfeng Tang Junjie Xu Hui Liu Suhang Wang 18 1 0 21 May 2023
PTGB: Pre-Train Graph Neural Networks for Brain Network Analysis Yi Yang Hejie Cui Carl Yang 35 18 0 20 May 2023