Towards Fine-Grained Explainability for Heterogeneous Graph Neural
Network

Towards Fine-Grained Explainability for Heterogeneous Graph Neural Network

23 December 2023

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Papers citing "Towards Fine-Grained Explainability for Heterogeneous Graph Neural Network"

11 / 11 papers shown

Title
Self-supervised Heterogeneous Graph Neural Network with Co-contrastive Learning Xiao Wang Nian Liu Hui-jun Han C. Shi SSL 71 390 0 19 May 2021
Higher-Order Attribute-Enhancing Heterogeneous Graph Neural Networks Jianxin Li Hao Peng Dongyuan Li Yingtong Dou Hekai Zhang Philip S. Yu Lifang He 66 80 0 16 Apr 2021
Generative Causal Explanations for Graph Neural Networks Wanyu Lin Hao Lan Baochun Li CML 59 176 0 14 Apr 2021
On Explainability of Graph Neural Networks via Subgraph Explorations Hao Yuan Haiyang Yu Jie Wang Kang Li Shuiwang Ji FAtt 83 390 0 09 Feb 2021
A Survey on Heterogeneous Graph Embedding: Methods, Techniques, Applications and Sources Xiao Wang Deyu Bo C. Shi Shaohua Fan Yanfang Ye Philip S. Yu AI4TS 89 306 0 30 Nov 2020
Interpreting Graph Neural Networks for NLP With Differentiable Edge Masking Michael Schlichtkrull Nicola De Cao Ivan Titov AI4CE 80 218 0 01 Oct 2020
Interpretable and Efficient Heterogeneous Graph Convolutional Network Yaming Yang Ziyu Guan Jianxin Li Wei Zhao Jiangtao Cui Quan Wang GNN 76 176 0 27 May 2020
MAGNN: Metapath Aggregated Graph Neural Network for Heterogeneous Graph Embedding Xinyu Fu Jiani Zhang Ziqiao Meng Irwin King 109 875 0 05 Feb 2020
Explainability Techniques for Graph Convolutional Networks Federico Baldassarre Hossein Azizpour GNN FAtt 174 270 0 31 May 2019
GNNExplainer: Generating Explanations for Graph Neural Networks Rex Ying Dylan Bourgeois Jiaxuan You Marinka Zitnik J. Leskovec LLMAG 150 1,323 0 10 Mar 2019
Modeling Relational Data with Graph Convolutional Networks Michael Schlichtkrull Thomas Kipf Peter Bloem Rianne van den Berg Ivan Titov Max Welling GNN 191 4,828 0 17 Mar 2017