A Meta-Learning Approach for Training Explainable Graph Neural Networks

20 September 2021

Papers citing "A Meta-Learning Approach for Training Explainable Graph Neural Networks"

6 / 6 papers shown

Title
A Review of Graph-Powered Data Quality Applications for IoT Monitoring Sensor Networks Pau Ferrer-Cid Jose M. Barcelo-Ordinas J. García-Vidal 42 2 0 28 Oct 2024
Combining Stochastic Explainers and Subgraph Neural Networks can Increase Expressivity and Interpretability Indro Spinelli Michele Guerra F. Bianchi Simone Scardapane 36 0 0 14 Apr 2023
Cluster-CAM: Cluster-Weighted Visual Interpretation of CNNs' Decision in Image Classification Zhenpeng Feng H. Ji M. Daković Xiyang Cui Mingzhe Zhu Ljubisa Stankovic 24 7 0 03 Feb 2023
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges M. Bronstein Joan Bruna Taco S. Cohen Petar Velivcković GNN 174 1,104 0 27 Apr 2021
Explainability in Graph Neural Networks: A Taxonomic Survey Hao Yuan Haiyang Yu Shurui Gui Shuiwang Ji 167 592 0 31 Dec 2020
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 329 11,681 0 09 Mar 2017