Edge-Level Explanations for Graph Neural Networks by Extending Explainability Methods for Convolutional Neural Networks

1 November 2021

Papers citing "Edge-Level Explanations for Graph Neural Networks by Extending Explainability Methods for Convolutional Neural Networks"

5 / 5 papers shown

Title
GRAM: An Interpretable Approach for Graph Anomaly Detection using Gradient Attention Maps Yifei Yang Peng Wang Xiaofan He Dongmian Zou 14 5 0 10 Nov 2023
XG-BoT: An Explainable Deep Graph Neural Network for Botnet Detection and Forensics Wai Weng Lo Gayan K. Kulatilleke Mohanad Sarhan S. Layeghy Marius Portmann 19 41 0 19 Jul 2022
Zorro: Valid, Sparse, and Stable Explanations in Graph Neural Networks Thorben Funke Megha Khosla Mandeep Rathee Avishek Anand FAtt 21 38 0 18 May 2021
Explainability in Graph Neural Networks: A Taxonomic Survey Hao Yuan Haiyang Yu Shurui Gui Shuiwang Ji 162 590 0 31 Dec 2020
Methods for Interpreting and Understanding Deep Neural Networks G. Montavon Wojciech Samek K. Müller FaML 234 2,233 0 24 Jun 2017