PGM-Explainer: Probabilistic Graphical Model Explanations for Graph Neural Networks

12 October 2020

Papers citing "PGM-Explainer: Probabilistic Graphical Model Explanations for Graph Neural Networks"

8 / 58 papers shown

Title
Towards Automated Evaluation of Explanations in Graph Neural Networks Bannihati Kumar Vanya Balaji Ganesan Aniket Saxena Devbrat Sharma Arvind Agarwal XAI GNN 24 4 0 22 Jun 2021
Probing GNN Explainers: A Rigorous Theoretical and Empirical Analysis of GNN Explanation Methods Chirag Agarwal Marinka Zitnik Himabindu Lakkaraju 24 51 0 16 Jun 2021
Zorro: Valid, Sparse, and Stable Explanations in Graph Neural Networks Thorben Funke Megha Khosla Mandeep Rathee Avishek Anand FAtt 23 38 0 18 May 2021
NCGNN: Node-Level Capsule Graph Neural Network for Semisupervised Classification Rui Yang Wenrui Dai Chenglin Li Junni Zou H. Xiong 28 20 0 07 Dec 2020
Higher-Order Explanations of Graph Neural Networks via Relevant Walks Thomas Schnake Oliver Eberle Jonas Lederer Shinichi Nakajima Kristof T. Schütt Klaus-Robert Muller G. Montavon 32 215 0 05 Jun 2020
Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks Minjie Wang Da Zheng Zihao Ye Quan Gan Mufei Li ... J. Zhao Haotong Zhang Alex Smola Jinyang Li Zheng-Wei Zhang AI4CE GNN 197 746 0 03 Sep 2019
Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation Jiaxuan You Bowen Liu Rex Ying Vijay S. Pande J. Leskovec GNN 203 885 0 07 Jun 2018
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 251 3,683 0 28 Feb 2017