Explaining the Explainers in Graph Neural Networks: a Comparative Study

27 October 2022

Papers citing "Explaining the Explainers in Graph Neural Networks: a Comparative Study"

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Title
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 85 0 0 08 Mar 2025
CAGN-GAT Fusion: A Hybrid Contrastive Attentive Graph Neural Network for Network Intrusion Detection Md Abrar Jahin Siyang Song M. F. Mridha Raihan Kabir Md. Rashedul Islam Yutaka Watanobe Hezerul Abdul Karim 71 0 0 02 Mar 2025
GraphXAIN: Narratives to Explain Graph Neural Networks Mateusz Cedro David Martens 110 0 0 04 Nov 2024
MAGE: Model-Level Graph Neural Networks Explanations via Motif-based Graph Generation Zhaoning Yu Hongyang Gao 77 3 0 21 May 2024
How Faithful are Self-Explainable GNNs? Marc Christiansen Lea Villadsen Zhiqiang Zhong Stefano Teso Davide Mottin 38 3 0 29 Aug 2023
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
Evaluating Explainability for Graph Neural Networks Chirag Agarwal Owen Queen Himabindu Lakkaraju Marinka Zitnik 74 107 0 19 Aug 2022
Encoding Concepts in Graph Neural Networks Lucie Charlotte Magister Pietro Barbiero Dmitry Kazhdan F. Siciliano Gabriele Ciravegna Fabrizio Silvestri M. Jamnik Pietro Lio 59 21 0 27 Jul 2022
A Survey of Explainable Graph Neural Networks: Taxonomy and Evaluation Metrics Yiqiao Li Jianlong Zhou Sunny Verma Fang Chen XAI 68 40 0 26 Jul 2022
Privacy and Transparency in Graph Machine Learning: A Unified Perspective Megha Khosla 48 4 0 22 Jul 2022
Pure Transformers are Powerful Graph Learners Jinwoo Kim Tien Dat Nguyen Seonwoo Min Sungjun Cho Moontae Lee Honglak Lee Seunghoon Hong 76 200 0 06 Jul 2022
Recipe for a General, Powerful, Scalable Graph Transformer Ladislav Rampášek Mikhail Galkin Vijay Prakash Dwivedi Anh Tuan Luu Guy Wolf Dominique Beaini 106 563 0 25 May 2022
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
Hierarchical Text-Conditional Image Generation with CLIP Latents Aditya A. Ramesh Prafulla Dhariwal Alex Nichol Casey Chu Mark Chen VLM DiffM 339 6,830 0 13 Apr 2022
Explainability in Graph Neural Networks: An Experimental Survey Peibo Li Yixing Yang Maurice Pagnucco Yang Song 46 31 0 17 Mar 2022
GCExplainer: Human-in-the-Loop Concept-based Explanations for Graph Neural Networks Lucie Charlotte Magister Dmitry Kazhdan Vikash Singh Pietro Lio 63 48 0 25 Jul 2021
Probing GNN Explainers: A Rigorous Theoretical and Empirical Analysis of GNN Explanation Methods Chirag Agarwal Marinka Zitnik Himabindu Lakkaraju 48 52 0 16 Jun 2021
Learning Equivariant Energy Based Models with Equivariant Stein Variational Gradient Descent P. Jaini Lars Holdijk Max Welling 60 11 0 15 Jun 2021
Higher-Order Attribute-Enhancing Heterogeneous Graph Neural Networks Jianxin Li Hao Peng Dongyuan Li Yingtong Dou Hekai Zhang Philip S. Yu Lifang He 58 80 0 16 Apr 2021
Generative Causal Explanations for Graph Neural Networks Wanyu Lin Hao Lan Baochun Li CML 59 175 0 14 Apr 2021
Combinatorial optimization and reasoning with graph neural networks Quentin Cappart Didier Chételat Elias Boutros Khalil Andrea Lodi Christopher Morris Petar Velickovic AI4CE 53 357 0 18 Feb 2021
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
CF-GNNExplainer: Counterfactual Explanations for Graph Neural Networks Ana Lucic Maartje ter Hoeve Gabriele Tolomei Maarten de Rijke Fabrizio Silvestri 141 145 0 05 Feb 2021
A Generalization of Transformer Networks to Graphs Vijay Prakash Dwivedi Xavier Bresson AI4CE 98 747 0 17 Dec 2020
Temporal Graph Networks for Deep Learning on Dynamic Graphs Emanuele Rossi B. Chamberlain Fabrizio Frasca D. Eynard Federico Monti M. Bronstein AI4CE 138 643 0 18 Jun 2020
XGNN: Towards Model-Level Explanations of Graph Neural Networks Haonan Yuan Jiliang Tang Xia Hu Shuiwang Ji 68 398 0 03 Jun 2020
Open Graph Benchmark: Datasets for Machine Learning on Graphs Weihua Hu Matthias Fey Marinka Zitnik Yuxiao Dong Hongyu Ren Bowen Liu Michele Catasta J. Leskovec 277 2,725 0 02 May 2020
Efficient Probabilistic Logic Reasoning with Graph Neural Networks Yuyu Zhang Xinshi Chen Yu’an Yang Arun Ramamurthy Yue Liu Yuan Qi Le Song AI4CE 109 111 0 29 Jan 2020
GraphLIME: Local Interpretable Model Explanations for Graph Neural Networks Q. Huang M. Yamada Yuan Tian Dinesh Singh Dawei Yin Yi-Ju Chang FAtt 69 352 0 17 Jan 2020
Graph Transformer Networks Seongjun Yun Minbyul Jeong Raehyun Kim Jaewoo Kang Hyunwoo J. Kim 127 970 0 06 Nov 2019
Layerwise Relevance Visualization in Convolutional Text Graph Classifiers Robert Schwarzenberg Marc Hübner David Harbecke Christoph Alt Leonhard Hennig FAtt GNN 45 70 0 24 Sep 2019
Explainability Techniques for Graph Convolutional Networks Federico Baldassarre Hossein Azizpour GNN FAtt 161 268 0 31 May 2019
Guiding High-Performance SAT Solvers with Unsat-Core Predictions Daniel Selsam Nikolaj S. Bjørner NAI 55 121 0 12 Mar 2019
GNNExplainer: Generating Explanations for Graph Neural Networks Rex Ying Dylan Bourgeois Jiaxuan You Marinka Zitnik J. Leskovec LLMAG 125 1,314 0 10 Mar 2019
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 885 5,493 0 20 Dec 2018
Towards Sparse Hierarchical Graph Classifiers Cătălina Cangea Petar Velickovic Nikola Jovanović Thomas Kipf Pietro Lio GNN 164 258 0 03 Nov 2018
Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks Christopher Morris Martin Ritzert Matthias Fey William L. Hamilton J. E. Lenssen Gaurav Rattan Martin Grohe GNN 171 1,630 0 04 Oct 2018
How Powerful are Graph Neural Networks? Keyulu Xu Weihua Hu J. Leskovec Stefanie Jegelka GNN 214 7,623 0 01 Oct 2018
A Survey Of Methods For Explaining Black Box Models Riccardo Guidotti A. Monreale Salvatore Ruggieri Franco Turini D. Pedreschi F. Giannotti XAI 120 3,938 0 06 Feb 2018
Inductive Representation Learning on Large Graphs William L. Hamilton Z. Ying J. Leskovec 452 15,179 0 07 Jun 2017
Neural Message Passing for Quantum Chemistry Justin Gilmer S. Schoenholz Patrick F. Riley Oriol Vinyals George E. Dahl 471 7,431 0 04 Apr 2017
Axiomatic Attribution for Deep Networks Mukund Sundararajan Ankur Taly Qiqi Yan OOD FAtt 175 5,968 0 04 Mar 2017
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization Ramprasaath R. Selvaraju Michael Cogswell Abhishek Das Ramakrishna Vedantam Devi Parikh Dhruv Batra FAtt 254 19,929 0 07 Oct 2016
node2vec: Scalable Feature Learning for Networks Aditya Grover J. Leskovec 183 10,856 0 03 Jul 2016
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering M. Defferrard Xavier Bresson P. Vandergheynst GNN 310 7,646 0 30 Jun 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 948 16,931 0 16 Feb 2016
Learning Deep Features for Discriminative Localization Bolei Zhou A. Khosla Àgata Lapedriza A. Oliva Antonio Torralba SSL SSeg FAtt 227 9,298 0 14 Dec 2015
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention Ke Xu Jimmy Ba Ryan Kiros Kyunghyun Cho Aaron Courville Ruslan Salakhutdinov R. Zemel Yoshua Bengio DiffM 314 10,050 0 10 Feb 2015
Striving for Simplicity: The All Convolutional Net Jost Tobias Springenberg Alexey Dosovitskiy Thomas Brox Martin Riedmiller FAtt 224 4,665 0 21 Dec 2014
Neural Machine Translation by Jointly Learning to Align and Translate Dzmitry Bahdanau Kyunghyun Cho Yoshua Bengio AIMat 505 27,263 0 01 Sep 2014