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Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional
  Networks

Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks

5 June 2019
Sitao Luan
Mingde Zhao
X. Chang
Doina Precup
    GNN
ArXivPDFHTML

Papers citing "Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks"

15 / 15 papers shown
Title
Curriculum-Enhanced Residual Soft An-Isotropic Normalization for
  Over-smoothness in Deep GNNs
Curriculum-Enhanced Residual Soft An-Isotropic Normalization for Over-smoothness in Deep GNNs
Jin Li
Qirong Zhang
Shuling Xu
Xinlong Chen
Longkun Guo
Yanglan Fu
21
0
0
13 Dec 2023
Dirichlet Energy Enhancement of Graph Neural Networks by Framelet
  Augmentation
Dirichlet Energy Enhancement of Graph Neural Networks by Framelet Augmentation
Jialin Chen
Yuelin Wang
Cristian Bodnar
Rex Ying
Pietro Lió
Yu Guang Wang
22
10
0
09 Nov 2023
Clarify Confused Nodes via Separated Learning
Clarify Confused Nodes via Separated Learning
Jiajun Zhou
Sheng Gong
Chenxuan Xie
Shanqing Yu
Qi Xuan
Xiaoniu Yang
Xiaoniu Yang
45
3
0
04 Jun 2023
Distributional Signals for Node Classification in Graph Neural Networks
Distributional Signals for Node Classification in Graph Neural Networks
Feng Ji
See Hian Lee
Kai Zhao
Wee Peng Tay
Jielong Yang
8
2
0
07 Apr 2023
Revisiting Over-smoothing and Over-squashing Using Ollivier-Ricci
  Curvature
Revisiting Over-smoothing and Over-squashing Using Ollivier-Ricci Curvature
K. Nguyen
Hieu Nong
T. Nguyen
Nhat Ho
Khuong N. Nguyen
Vinh Phu Nguyen
13
61
0
28 Nov 2022
Skeleton-based Action Recognition via Temporal-Channel Aggregation
Skeleton-based Action Recognition via Temporal-Channel Aggregation
Shengqin Wang
Yongji Zhang
M. Zhao
Hong Qi
Kai Wang
Fenglin Wei
Yu Jiang
23
22
0
31 May 2022
SStaGCN: Simplified stacking based graph convolutional networks
SStaGCN: Simplified stacking based graph convolutional networks
Jia Cai
Zhilong Xiong
Shaogao Lv
GNN
30
1
0
16 Nov 2021
Cold Brew: Distilling Graph Node Representations with Incomplete or
  Missing Neighborhoods
Cold Brew: Distilling Graph Node Representations with Incomplete or Missing Neighborhoods
Wenqing Zheng
Edward W. Huang
Nikhil S. Rao
S. Katariya
Zhangyang Wang
Karthik Subbian
21
61
0
08 Nov 2021
Is Heterophily A Real Nightmare For Graph Neural Networks To Do Node
  Classification?
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
30
110
0
12 Sep 2021
Sampling methods for efficient training of graph convolutional networks:
  A survey
Sampling methods for efficient training of graph convolutional networks: A survey
Xin Liu
Mingyu Yan
Lei Deng
Guoqi Li
Xiaochun Ye
Dongrui Fan
GNN
21
95
0
10 Mar 2021
GraphCL: Contrastive Self-Supervised Learning of Graph Representations
GraphCL: Contrastive Self-Supervised Learning of Graph Representations
H. Hafidi
Mounir Ghogho
P. Ciblat
A. Swami
SSL
12
53
0
15 Jul 2020
Optimization and Generalization Analysis of Transduction through
  Gradient Boosting and Application to Multi-scale Graph Neural Networks
Optimization and Generalization Analysis of Transduction through Gradient Boosting and Application to Multi-scale Graph Neural Networks
Kenta Oono
Taiji Suzuki
AI4CE
14
31
0
15 Jun 2020
Principal Neighbourhood Aggregation for Graph Nets
Principal Neighbourhood Aggregation for Graph Nets
Gabriele Corso
Luca Cavalleri
Dominique Beaini
Pietro Lió
Petar Velickovic
GNN
6
648
0
12 Apr 2020
Geometric deep learning on graphs and manifolds using mixture model CNNs
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
1,801
0
25 Nov 2016
Geometric deep learning: going beyond Euclidean data
Geometric deep learning: going beyond Euclidean data
M. Bronstein
Joan Bruna
Yann LeCun
Arthur Szlam
P. Vandergheynst
GNN
231
3,202
0
24 Nov 2016
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