D4Explainer: In-Distribution GNN Explanations via Discrete Denoising Diffusion

30 October 2023

Papers citing "D4Explainer: In-Distribution GNN Explanations via Discrete Denoising Diffusion"

9 / 9 papers shown

Title
PowerGraph: A power grid benchmark dataset for graph neural networks Anna Varbella Kenza Amara B. Gjorgiev Mennatallah El-Assady G. Sansavini 20 5 0 05 Feb 2024
Generative Explanations for Graph Neural Network: Methods and Evaluations Jialin Chen Kenza Amara Junchi Yu Rex Ying 39 3 0 09 Nov 2023
DAG Matters! GFlowNets Enhanced Explainer For Graph Neural Networks Wenqian Li Yinchuan Li Zhigang Li Jianye Hao Yan Pang 85 29 0 04 Mar 2023
Diffusion Models for Graphs Benefit From Discrete State Spaces K. Haefeli Karolis Martinkus Nathanael Perraudin Roger Wattenhofer DiffM 85 52 0 04 Oct 2022
A Survey on Generative Diffusion Model Hanqun Cao Cheng Tan Zhangyang Gao Yilun Xu Guangyong Chen Pheng-Ann Heng Stan Z. Li MedIm 37 206 0 06 Sep 2022
CF-GNNExplainer: Counterfactual Explanations for Graph Neural Networks Ana Lucic Maartje ter Hoeve Gabriele Tolomei Maarten de Rijke Fabrizio Silvestri 110 142 0 05 Feb 2021
Explainability in Graph Neural Networks: A Taxonomic Survey Hao Yuan Haiyang Yu Shurui Gui Shuiwang Ji 167 591 0 31 Dec 2020
Geom-GCN: Geometric Graph Convolutional Networks Hongbin Pei Bingzhen Wei Kevin Chen-Chuan Chang Yu Lei Bo Yang GNN 169 1,078 0 13 Feb 2020
MoleculeNet: A Benchmark for Molecular Machine Learning Zhenqin Wu Bharath Ramsundar Evan N. Feinberg Joseph Gomes C. Geniesse Aneesh S. Pappu K. Leswing Vijay S. Pande OOD 169 1,775 0 02 Mar 2017