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Training Matters: Unlocking Potentials of Deeper Graph Convolutional Neural Networks

20 August 2020

Sitao Luan

Papers citing "Training Matters: Unlocking Potentials of Deeper Graph Convolutional Neural Networks"

21 / 21 papers shown

Title
On Addressing the Limitations of Graph Neural Networks Sitao Luan GNN 68 5 0 22 Jun 2023
Complete the Missing Half: Augmenting Aggregation Filtering with Diversification for Graph Convolutional Neural Networks Sitao Luan Mingde Zhao Chenqing Hua Xiao-Wen Chang Doina Precup GNN 59 34 0 21 Dec 2022
Revisiting Heterophily For Graph Neural Networks Sitao Luan Chenqing Hua Qincheng Lu Jiaqi Zhu Mingde Zhao Shuyuan Zhang Xiaoming Chang Doina Precup 76 197 0 14 Oct 2022
Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods Derek Lim Felix Hohne Xiuyu Li Sijia Huang Vaishnavi Gupta Omkar Bhalerao Ser-Nam Lim 125 359 0 27 Oct 2021
Is Heterophily A Real Nightmare For Graph Neural Networks To Do Node Classification? Sitao Luan Chenqing Hua Qincheng Lu Jiaqi Zhu Mingde Zhao Shuyuan Zhang Xiaoming Chang Doina Precup 90 115 0 12 Sep 2021
Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks Sitao Luan Mingde Zhao Xiao-Wen Chang Doina Precup GNN 78 157 0 05 Jun 2019
DeepGCNs: Can GCNs Go as Deep as CNNs? Ge Li Matthias Muller Ali K. Thabet Guohao Li 3DPC GNN 130 1,350 0 07 Apr 2019
LanczosNet: Multi-Scale Deep Graph Convolutional Networks Renjie Liao Zhizhen Zhao R. Urtasun R. Zemel GNN 84 228 0 06 Jan 2019
FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling Jie Chen Tengfei Ma Cao Xiao GNN 149 1,517 0 30 Jan 2018
Deeper Insights into Graph Convolutional Networks for Semi-Supervised Learning Qimai Li Zhichao Han Xiao-Ming Wu GNN SSL 194 2,830 0 22 Jan 2018
Stochastic Training of Graph Convolutional Networks with Variance Reduction Jianfei Chen Jun Zhu Le Song GNN BDL 67 31 0 29 Oct 2017
Inductive Representation Learning on Large Graphs William L. Hamilton Z. Ying J. Leskovec 514 15,319 0 07 Jun 2017
Neural Message Passing for Quantum Chemistry Justin Gilmer S. Schoenholz Patrick F. Riley Oriol Vinyals George E. Dahl 598 7,488 0 04 Apr 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 421 1,824 0 25 Nov 2016
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 813 3,293 0 24 Nov 2016
Semi-Supervised Classification with Graph Convolutional Networks Thomas Kipf Max Welling GNN SSL 665 29,156 0 09 Sep 2016
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering M. Defferrard Xavier Bresson P. Vandergheynst GNN 360 7,671 0 30 Jun 2016
Revisiting Semi-Supervised Learning with Graph Embeddings Zhilin Yang William W. Cohen Ruslan Salakhutdinov GNN SSL 174 2,105 0 29 Mar 2016
Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks Tim Salimans Diederik P. Kingma ODL 196 1,943 0 25 Feb 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.2K 194,426 0 10 Dec 2015
The Emerging Field of Signal Processing on Graphs: Extending High-Dimensional Data Analysis to Networks and Other Irregular Domains D. Shuman S. K. Narang P. Frossard Antonio Ortega P. Vandergheynst 138 3,979 0 31 Oct 2012