On Addressing the Limitations of Graph Neural Networks

On Addressing the Limitations of Graph Neural Networks

22 June 2023

Sitao Luan

Papers citing "On Addressing the Limitations of Graph Neural Networks"

8 / 8 papers shown

Title
Transfer Entropy in Graph Convolutional Neural Networks Adrian Moldovan A. Cataron Razvan Andonie GNN 23 1 0 08 Jun 2024
When Do We Need Graph Neural Networks for Node Classification? Sitao Luan Chenqing Hua Qincheng Lu Jiaqi Zhu Xiaoming Chang Doina Precup 22 0 0 30 Oct 2022
Beyond Low-frequency Information in Graph Convolutional Networks Deyu Bo Xiao Wang C. Shi Huawei Shen GNN 87 556 0 04 Jan 2021
Training Matters: Unlocking Potentials of Deeper Graph Convolutional Neural Networks Sitao Luan Mingde Zhao X. Chang Doina Precup GNN 13 9 0 20 Aug 2020
Geom-GCN: Geometric Graph Convolutional Networks Hongbin Pei Bingzhen Wei Kevin Chen-Chuan Chang Yu Lei Bo Yang GNN 169 1,077 0 13 Feb 2020
Representation Learning on Graphs with Jumping Knowledge Networks Keyulu Xu Chengtao Li Yonglong Tian Tomohiro Sonobe Ken-ichi Kawarabayashi Stefanie Jegelka GNN 229 1,941 0 09 Jun 2018
Geometric deep learning on graphs and manifolds using mixture model CNNs Federico Monti Davide Boscaini Jonathan Masci Emanuele Rodolà Jan Svoboda M. Bronstein GNN 234 1,811 0 25 Nov 2016
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 236 3,234 0 24 Nov 2016