Parameterized Explainer for Graph Neural Network

9 November 2020

Dongkuan Xu

Papers citing "Parameterized Explainer for Graph Neural Network"

50 / 288 papers shown

Title
Dynamic Causal Explanation Based Diffusion-Variational Graph Neural Network for Spatio-temporal Forecasting G. Liang Prayag Tiwari Sławomir Nowaczyk Stefan Byttner F. Alonso-Fernandez DiffM 33 11 0 16 May 2023
Survey of Malware Analysis through Control Flow Graph using Machine Learning Shaswata Mitra Stephen Torri Sudip Mittal 30 5 0 15 May 2023
Towards Understanding the Generalization of Graph Neural Networks Huayi Tang Y. Liu GNN AI4CE 32 29 0 14 May 2023
Unstructured and structured data: Can we have the best of both worlds with large language models? W. Tan 11 1 0 25 Apr 2023
Generating Post-hoc Explanations for Skip-gram-based Node Embeddings by Identifying Important Nodes with Bridgeness Hogun Park Jennifer Neville 11 4 0 24 Apr 2023
Explanations of Black-Box Models based on Directional Feature Interactions A. Masoomi Davin Hill Zhonghui Xu C. Hersh E. Silverman P. Castaldi Stratis Ioannidis Jennifer Dy FAtt 21 17 0 16 Apr 2023
Combining Stochastic Explainers and Subgraph Neural Networks can Increase Expressivity and Interpretability Indro Spinelli Michele Guerra F. Bianchi Simone Scardapane 25 0 0 14 Apr 2023
Inductive Graph Unlearning Cheng-Long Wang Mengdi Huai Di Wang MU 11 22 0 06 Apr 2023
Rethinking the Trigger-injecting Position in Graph Backdoor Attack Jing Xu Gorka Abad S. Picek LLMSV SILM 19 6 0 05 Apr 2023
The expressive power of pooling in Graph Neural Networks F. Bianchi Veronica Lachi 14 29 0 04 Apr 2023
Counterfactual Learning on Graphs: A Survey Zhimeng Guo Teng Xiao Zongyu Wu Charu C. Aggarwal Hui Liu Suhang Wang CML AI4CE 38 18 0 03 Apr 2023
A Survey on Malware Detection with Graph Representation Learning Tristan Bilot Nour El Madhoun Khaldoun Al Agha Anis Zouaoui AAML 13 20 0 28 Mar 2023
Illuminati: Towards Explaining Graph Neural Networks for Cybersecurity Analysis Haoyu He Yuede Ji H. H. Huang 20 20 0 26 Mar 2023
Time Series Contrastive Learning with Information-Aware Augmentations Dongsheng Luo Wei Cheng Yingheng Wang Dongkuan Xu Jingchao Ni ... Xuchao Zhang Yanchi Liu Yuncong Chen Haifeng Chen Xiang Zhang AI4TS 24 55 0 21 Mar 2023
Distill n' Explain: explaining graph neural networks using simple surrogates Tamara A. Pereira Erik Nasciment Lucas Resck Diego Mesquita Amauri Souza 22 15 0 17 Mar 2023
DAG Matters! GFlowNets Enhanced Explainer For Graph Neural Networks Wenqian Li Yinchuan Li Zhigang Li Jianye Hao Yan Pang 83 29 0 04 Mar 2023
PaGE-Link: Path-based Graph Neural Network Explanation for Heterogeneous Link Prediction Shichang Zhang Jiani Zhang Xiang Song Soji Adeshina Da Zheng Christos Faloutsos Yizhou Sun LRM 19 31 0 24 Feb 2023
Self-Supervised Temporal Graph learning with Temporal and Structural Intensity Alignment Meng Liu K. Liang Bin Xiao Wenxuan Tu Sihang Zhou Xihong Yang Xinwang Liu Yue Liu 18 68 0 15 Feb 2023
Adversarial Learning Data Augmentation for Graph Contrastive Learning in Recommendation Junjie Huang Qi Cao Ruobing Xie Shaoliang Zhang Feng Xia Huawei Shen Xueqi Cheng 16 9 0 05 Feb 2023
Structural Explanations for Graph Neural Networks using HSIC Ayato Toyokuni Makoto Yamada 19 1 0 04 Feb 2023
Graph Neural Networks for temporal graphs: State of the art, open challenges, and opportunities Antonio Longa Veronica Lachi G. Santin Monica Bianchini Bruno Lepri Pietro Lió F. Scarselli Andrea Passerini AI4CE 13 50 0 02 Feb 2023
State of the Art and Potentialities of Graph-level Learning Zhenyu Yang Ge Zhang Jia Wu Jian Yang Quan.Z Sheng ... Charu C. Aggarwal Hao Peng Wenbin Hu Edwin R. Hancock Pietro Lio' GNN AI4CE 30 10 0 14 Jan 2023
Faithful and Consistent Graph Neural Network Explanations with Rationale Alignment Tianxiang Zhao Dongsheng Luo Xiang Zhang Suhang Wang 21 7 0 07 Jan 2023
Rethinking Explaining Graph Neural Networks via Non-parametric Subgraph Matching Fang Wu Siyuan Li Xurui Jin Yinghui Jiang Dragomir R. Radev Z. Niu Stan Z. Li 22 10 0 07 Jan 2023
CI-GNN: A Granger Causality-Inspired Graph Neural Network for Interpretable Brain Network-Based Psychiatric Diagnosis Kaizhong Zheng Shujian Yu Badong Chen CML 21 31 0 04 Jan 2023
GANExplainer: GAN-based Graph Neural Networks Explainer Yiqiao Li Jianlong Zhou Boyuan Zheng Fang Chen LLMAG 29 4 0 30 Dec 2022
Graph Learning and Its Advancements on Large Language Models: A Holistic Survey Shaopeng Wei Yu Zhao Xingyan Chen Qing Li Fuzhen Zhuang Ji Liu Fuji Ren Gang Kou AI4CE 19 5 0 17 Dec 2022
TopoImb: Toward Topology-level Imbalance in Learning from Graphs Tianxiang Zhao Dongsheng Luo Xiang Zhang Suhang Wang AI4CE 28 11 0 16 Dec 2022
Towards Explainable Motion Prediction using Heterogeneous Graph Representations Sandra Carrasco Limeros Sylwia Majchrowska Joakim Johnander Christoffer Petersson David Fernández Llorca 29 15 0 07 Dec 2022
On the Limit of Explaining Black-box Temporal Graph Neural Networks Minh Nhat Vu My T. Thai 11 4 0 02 Dec 2022
xEM: Explainable Entity Matching in Customer 360 Sukriti Jaitly Deepa Mariam George Balaji Ganesan Muhammad Ameen Srinivas Pusapati 16 0 0 01 Dec 2022
Towards Training GNNs using Explanation Directed Message Passing V. Giunchiglia Chirag Varun Shukla Guadalupe Gonzalez Chirag Agarwal 25 7 0 30 Nov 2022
Interpreting Unfairness in Graph Neural Networks via Training Node Attribution Yushun Dong Song Wang Jing Ma Ninghao Liu Jundong Li 40 21 0 25 Nov 2022
MEGAN: Multi-Explanation Graph Attention Network Jonas Teufel Luca Torresi Patrick Reiser Pascal Friederich 16 8 0 23 Nov 2022
Cross-Mode Knowledge Adaptation for Bike Sharing Demand Prediction using Domain-Adversarial Graph Neural Networks Yuebing Liang Guan Huang Zhan Zhao OOD 21 14 0 16 Nov 2022
INGREX: An Interactive Explanation Framework for Graph Neural Networks Tien-Cuong Bui Van-Duc Le Wen-Syan Li S. Cha 17 0 0 03 Nov 2022
PAGE: Prototype-Based Model-Level Explanations for Graph Neural Networks Yong-Min Shin Sun-Woo Kim Won-Yong Shin 21 4 0 31 Oct 2022
Interpretable Geometric Deep Learning via Learnable Randomness Injection Siqi Miao Yunan Luo Miaoyuan Liu Pan Li 19 25 0 30 Oct 2022
Explaining the Explainers in Graph Neural Networks: a Comparative Study Antonio Longa Steve Azzolin G. Santin G. Cencetti Pietro Lio' Bruno Lepri Andrea Passerini 46 27 0 27 Oct 2022
A Survey on Graph Counterfactual Explanations: Definitions, Methods, Evaluation, and Research Challenges Mario Alfonso Prado-Romero Bardh Prenkaj Giovanni Stilo F. Giannotti CML 27 30 0 21 Oct 2022
Global Counterfactual Explainer for Graph Neural Networks Mert Kosan Zexi Huang Sourav Medya Sayan Ranu Ambuj K. Singh 19 47 0 21 Oct 2022
Toward Multiple Specialty Learners for Explaining GNNs via Online Knowledge Distillation Tien-Cuong Bui Van-Duc Le Wen-Syan Li S. Cha 15 3 0 20 Oct 2022
Global Explainability of GNNs via Logic Combination of Learned Concepts Steve Azzolin Antonio Longa Pietro Barbiero Pietro Lio' Andrea Passerini 25 54 0 13 Oct 2022
Variational Graph Generator for Multi-View Graph Clustering Jianpeng Chen Yawen Ling Jie Xu Yazhou Ren Shudong Huang X. Pu Zhifeng Hao Philip S. Yu Lifang He 17 5 0 13 Oct 2022
Towards Prototype-Based Self-Explainable Graph Neural Network Enyan Dai Suhang Wang 25 12 0 05 Oct 2022
Spectral Augmentation for Self-Supervised Learning on Graphs Lu Lin Jinghui Chen Hongning Wang OOD 32 48 0 02 Oct 2022
L2XGNN: Learning to Explain Graph Neural Networks G. Serra Mathias Niepert 26 7 0 28 Sep 2022
Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure Shaohua Fan Xiao Wang Yanhu Mo Chuan Shi Jian Tang CML OOD AI4CE 31 89 0 28 Sep 2022
Explainability in subgraphs-enhanced Graph Neural Networks Michele Guerra Indro Spinelli Simone Scardapane F. Bianchi 16 1 0 16 Sep 2022
GNNInterpreter: A Probabilistic Generative Model-Level Explanation for Graph Neural Networks Xiaoqi Wang Hang Shen 22 41 0 15 Sep 2022