Higher-Order Explanations of Graph Neural Networks via Relevant Walks

5 June 2020

Papers citing "Higher-Order Explanations of Graph Neural Networks via Relevant Walks"

50 / 111 papers shown

Title
Uncovering the Structure of Explanation Quality with Spectral Analysis Johannes Maeß G. Montavon Shinichi Nakajima Klaus-Robert Müller Thomas Schnake FAtt 38 0 0 11 Apr 2025
Recent Advances in Malware Detection: Graph Learning and Explainability Hossein Shokouhinejad Roozbeh Razavi-Far Hesamodin Mohammadian Mahdi Rabbani Samuel Ansong Griffin Higgins Ali Ghorbani AAML 70 2 0 14 Feb 2025
xMIL: Insightful Explanations for Multiple Instance Learning in Histopathology Julius Hense M. J. Idaji Oliver Eberle Thomas Schnake Jonas Dippel Laure Ciernik Oliver Buchstab Andreas Mock Frederick Klauschen Klaus-Robert Müller 49 3 0 08 Jan 2025
xCG: Explainable Cell Graphs for Survival Prediction in Non-Small Cell Lung Cancer Marvin Sextro Gabriel Dernbach Kai Standvoss S. Schallenberg Frederick Klauschen Klaus-Robert Müller Maximilian Alber Lukas Ruff 30 0 0 12 Nov 2024
MBExplainer: Multilevel bandit-based explanations for downstream models with augmented graph embeddings Ashkan Golgoon Ryan Franks Khashayar Filom Arjun Ravi Kannan 33 0 0 01 Nov 2024
Disentangled and Self-Explainable Node Representation Learning Simone Piaggesi Andre' Panisson Megha Khosla 31 0 0 28 Oct 2024
Deeper Insights into Deep Graph Convolutional Networks: Stability and Generalization Guangrui Yang Ming Li Han Feng Xiaosheng Zhuang GNN OOD BDL 35 2 0 11 Oct 2024
StagedVulBERT: Multi-Granular Vulnerability Detection with a Novel Pre-trained Code Model Yuan Jiang Yujian Zhang Xiaohong Su Christoph Treude Tiantian Wang 45 0 0 08 Oct 2024
Dumpling GNN: Hybrid GNN Enables Better ADC Payload Activity Prediction Based on Chemical Structure Shengjie Xu Lingxi Xie 23 0 0 23 Sep 2024
Towards Symbolic XAI -- Explanation Through Human Understandable Logical Relationships Between Features Thomas Schnake Farnoush Rezaei Jafaria Jonas Lederer Ping Xiong Shinichi Nakajima Stefan Gugler G. Montavon Klaus-Robert Müller 40 3 0 30 Aug 2024
The Clever Hans Effect in Unsupervised Learning Jacob R. Kauffmann Jonas Dippel Lukas Ruff Wojciech Samek Klaus-Robert Müller G. Montavon SSL CML HAI 34 1 0 15 Aug 2024
Towards Understanding Sensitive and Decisive Patterns in Explainable AI: A Case Study of Model Interpretation in Geometric Deep Learning Jiajun Zhu Siqi Miao Rex Ying Pan Li 38 1 0 30 Jun 2024
Demystifying Higher-Order Graph Neural Networks Maciej Besta Florian Scheidl Lukas Gianinazzi S. Klaiman Jürgen Müller Torsten Hoefler 43 2 0 18 Jun 2024
Generating Human Understandable Explanations for Node Embeddings Zohair Shafi Ayan Chatterjee Tina Eliassi-Rad 31 1 0 11 Jun 2024
MambaLRP: Explaining Selective State Space Sequence Models F. Jafari G. Montavon Klaus-Robert Müller Oliver Eberle Mamba 59 9 0 11 Jun 2024
Explainable Graph Neural Networks Under Fire Zhong Li Simon Geisler Yuhang Wang Stephan Günnemann M. Leeuwen AAML 40 0 0 10 Jun 2024
Progressive Inference: Explaining Decoder-Only Sequence Classification Models Using Intermediate Predictions Sanjay Kariyappa Freddy Lecue Saumitra Mishra Christopher Pond Daniele Magazzeni Manuela Veloso 37 1 0 03 Jun 2024
From Latent to Lucid: Transforming Knowledge Graph Embeddings into Interpretable Structures with KGEPrisma Christoph Wehner Chrysa Iliopoulou Ute Schmid Tarek R. Besold 58 0 0 03 Jun 2024
Explaining Graph Neural Networks via Structure-aware Interaction Index Ngoc H. Bui Hieu Trung Nguyen Viet Anh Nguyen Rex Ying FAtt 40 4 0 23 May 2024
MAGE: Model-Level Graph Neural Networks Explanations via Motif-based Graph Generation Zhaoning Yu Hongyang Gao 42 3 0 21 May 2024
Higher-order Spatio-temporal Physics-incorporated Graph Neural Network for Multivariate Time Series Imputation Guojun Liang Prayag Tiwari Slawomir Nowaczyk Stefan Byttner AI4TS AI4CE 52 3 0 16 May 2024
Explaining Text Similarity in Transformer Models Alexandros Vasileiou Oliver Eberle 43 7 0 10 May 2024
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
Graph Neural Networks for Vulnerability Detection: A Counterfactual Explanation Zhaoyang Chu Yao Wan Qian Li Yang Wu Hongyu Zhang Yulei Sui Guandong Xu Hai Jin AAML 38 9 0 24 Apr 2024
Sparse Explanations of Neural Networks Using Pruned Layer-Wise Relevance Propagation Paulo Yanez Sarmiento Simon Witzke Nadja Klein Bernhard Y. Renard FAtt AAML 38 0 0 22 Apr 2024
A Differential Geometric View and Explainability of GNN on Evolving Graphs Yazheng Liu Xi Zhang Sihong Xie 19 3 0 11 Mar 2024
Predicting Instability in Complex Oscillator Networks: Limitations and Potentials of Network Measures and Machine Learning Christian Nauck M. Lindner Nora Molkenthin Jürgen Kurths Eckehard Scholl Jorg Raisch Frank Hellmann 18 1 0 27 Feb 2024
Explaining Predictive Uncertainty by Exposing Second-Order Effects Florian Bley Sebastian Lapuschkin Wojciech Samek G. Montavon 29 2 0 30 Jan 2024
GOAt: Explaining Graph Neural Networks via Graph Output Attribution Shengyao Lu Keith G. Mills Jiao He Bang Liu Di Niu FAtt 31 8 0 26 Jan 2024
GNNShap: Scalable and Accurate GNN Explanation using Shapley Values Selahattin Akkas Ariful Azad FAtt 34 3 0 09 Jan 2024
Verifying Relational Explanations: A Probabilistic Approach Abisha Thapa Magar Anup Shakya Somdeb Sarkhel Deepak Venugopal 17 0 0 05 Jan 2024
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
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 Tianqianjin Lin Kaisong Song Zhuoren Jiang Yangyang Kang Weikang Yuan Xurui Li Changlong Sun Cui Huang Xiaozhong Liu 38 6 0 10 Dec 2023
Everybody Needs a Little HELP: Explaining Graphs via Hierarchical Concepts Jonas Jürß Lucie Charlotte Magister Pietro Barbiero Pietro Lió Nikola Simidjievski 38 1 0 25 Nov 2023
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 29 5 0 25 Nov 2023
TempME: Towards the Explainability of Temporal Graph Neural Networks via Motif Discovery Jialin Chen Rex Ying AI4TS 21 20 0 30 Oct 2023
D4Explainer: In-Distribution GNN Explanations via Discrete Denoising Diffusion Jialin Chen Shirley Wu Abhijit Gupta Rex Ying DiffM 39 4 0 30 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
Transitivity Recovering Decompositions: Interpretable and Robust Fine-Grained Relationships Abhra Chaudhuri Massimiliano Mancini Zeynep Akata Anjan Dutta 21 2 0 24 Oct 2023
Insightful analysis of historical sources at scales beyond human capabilities using unsupervised Machine Learning and XAI Oliver Eberle Jochen Büttner Hassan el-Hajj G. Montavon Klaus-Robert Muller Matteo Valleriani 19 1 0 13 Oct 2023
GradXKG: A Universal Explain-per-use Temporal Knowledge Graph Explainer Chenhan Yuan Hoda Eldardiry 18 0 0 07 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 29 13 0 03 Oct 2023
On the Robustness of Post-hoc GNN Explainers to Label Noise Zhiqiang Zhong Yangqianzi Jiang Davide Mottin AAML NoLa 29 3 0 04 Sep 2023
Semantic Interpretation and Validation of Graph Attention-based Explanations for GNN Models Efimia Panagiotaki D. Martini Lars Kunze 11 4 0 08 Aug 2023
Machine Learning Small Molecule Properties in Drug Discovery Nikolai Schapin Maciej Majewski Alejandro Varela-Rial C. Arroniz Gianni de Fabritiis 14 9 0 02 Aug 2023
Counterfactual Explanations for Graph Classification Through the Lenses of Density Carlo Abrate Giulia Preti Francesco Bonchi 18 1 0 27 Jul 2023
Globally Interpretable Graph Learning via Distribution Matching Yi Nian Yurui Chang Wei Jin Lu Lin OOD 58 4 0 18 Jun 2023
Efficient GNN Explanation via Learning Removal-based Attribution Yao Rong Guanchu Wang Qizhang Feng Ninghao Liu Zirui Liu Enkelejda Kasneci Xia Hu 15 9 0 09 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 25 1 0 03 Jun 2023