A simple yet effective baseline for non-attributed graph classification

8 November 2018

Papers citing "A simple yet effective baseline for non-attributed graph classification"

10 / 10 papers shown

Title
Observe Locally, Classify Globally: Using GNNs to Identify Sparse Matrix Structure Khaled Abdelaal Richard Veras 17 1 0 26 Jul 2023
A Comparison of Graph Neural Networks for Malware Classification Vrinda Malhotra Katerina Potika Mark Stamp 24 3 0 22 Mar 2023
Optimizing DNN Compilation for Distributed Training with Joint OP and Tensor Fusion Xiaodong Yi Shiwei Zhang Lansong Diao Chuan Wu Zhen Zheng Shiqing Fan Siyu Wang Jun Yang W. Lin 18 4 0 26 Sep 2022
MOOMIN: Deep Molecular Omics Network for Anti-Cancer Drug Combination Therapy Benedek Rozemberczki A. Gogleva S. Nilsson G. Edwards A. Nikolov Eliseo Papa GNN 23 19 0 28 Oct 2021
Capsule Graph Neural Networks with EM Routing Yu Lei Jing Zhang GNN 18 5 0 18 Oct 2021
Joint Embedding of Structural and Functional Brain Networks with Graph Neural Networks for Mental Illness Diagnosis Yanqiao Zhu Hejie Cui Lifang He Lichao Sun Carl Yang 12 36 0 07 Jul 2021
On Positional and Structural Node Features for Graph Neural Networks on Non-attributed Graphs Hejie Cui Zijie Lu Pan Li Carl Yang 13 80 0 03 Jul 2021
The Shapley Value of Classifiers in Ensemble Games Benedek Rozemberczki Rik Sarkar FAtt FedML TDI 51 33 0 06 Jan 2021
Fast Graph Representation Learning with PyTorch Geometric Matthias Fey J. E. Lenssen 3DH GNN 3DPC 68 4,223 0 06 Mar 2019
Simplifying Graph Convolutional Networks Felix Wu Tianyi Zhang Amauri Souza Christopher Fifty Tao Yu Kilian Q. Weinberger GNN 9 3,109 0 19 Feb 2019