PAGE: Prototype-Based Model-Level Explanations for Graph Neural Networks

31 October 2022

Papers citing "PAGE: Prototype-Based Model-Level Explanations for Graph Neural Networks"

6 / 6 papers shown

Title
Quantifying the Intrinsic Usefulness of Attributional Explanations for Graph Neural Networks with Artificial Simulatability Studies Jonas Teufel Luca Torresi Pascal Friederich FAtt 28 1 0 25 May 2023
MEGAN: Multi-Explanation Graph Attention Network Jonas Teufel Luca Torresi Patrick Reiser Pascal Friederich 26 8 0 23 Nov 2022
CF-GNNExplainer: Counterfactual Explanations for Graph Neural Networks Ana Lucic Maartje ter Hoeve Gabriele Tolomei Maarten de Rijke Fabrizio Silvestri 118 142 0 05 Feb 2021
Explainability in Graph Neural Networks: A Taxonomic Survey Hao Yuan Haiyang Yu Shurui Gui Shuiwang Ji 167 593 0 31 Dec 2020
Methods for Interpreting and Understanding Deep Neural Networks G. Montavon Wojciech Samek K. Müller FaML 234 2,238 0 24 Jun 2017
Geometric deep learning on graphs and manifolds using mixture model CNNs Federico Monti Davide Boscaini Jonathan Masci Emanuele Rodolà Jan Svoboda M. Bronstein GNN 251 1,811 0 25 Nov 2016