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N-GCN: Multi-scale Graph Convolution for Semi-supervised Node
  Classification

N-GCN: Multi-scale Graph Convolution for Semi-supervised Node Classification

24 February 2018
Sami Abu-El-Haija
Amol Kapoor
Bryan Perozzi
Joonseok Lee
    GNN
    SSL
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Papers citing "N-GCN: Multi-scale Graph Convolution for Semi-supervised Node Classification"

41 / 91 papers shown
Title
Reliable Graph Neural Networks via Robust Aggregation
Reliable Graph Neural Networks via Robust Aggregation
Simon Geisler
Daniel Zügner
Stephan Günnemann
AAML
OOD
8
71
0
29 Oct 2020
On the Equivalence of Decoupled Graph Convolution Network and Label
  Propagation
On the Equivalence of Decoupled Graph Convolution Network and Label Propagation
Hande Dong
Jiawei Chen
Fuli Feng
Xiangnan He
Shuxian Bi
Zhaolin Ding
Peng Cui
BDL
35
102
0
23 Oct 2020
Lightweight, Dynamic Graph Convolutional Networks for AMR-to-Text
  Generation
Lightweight, Dynamic Graph Convolutional Networks for AMR-to-Text Generation
Yan Zhang
Zhijiang Guo
Zhiyang Teng
Wei Lu
Shay B. Cohen
Zuozhu Liu
Lidong Bing
GNN
24
18
0
09 Oct 2020
Semi-Supervised Node Classification by Graph Convolutional Networks and
  Extracted Side Information
Semi-Supervised Node Classification by Graph Convolutional Networks and Extracted Side Information
Mohammadjafar Esmaeili
Aria Nosratinia
GNN
21
1
0
29 Sep 2020
AEGCN: An Autoencoder-Constrained Graph Convolutional Network
AEGCN: An Autoencoder-Constrained Graph Convolutional Network
Mingyuan Ma
Sen Na
Hongyu Wang
GNN
29
28
0
03 Jul 2020
Scaling Graph Neural Networks with Approximate PageRank
Scaling Graph Neural Networks with Approximate PageRank
Aleksandar Bojchevski
Johannes Klicpera
Bryan Perozzi
Amol Kapoor
Martin J. Blais
Benedek Rozemberczki
Michal Lukasik
Stephan Günnemann
GNN
32
367
0
03 Jul 2020
From Spectrum Wavelet to Vertex Propagation: Graph Convolutional
  Networks Based on Taylor Approximation
From Spectrum Wavelet to Vertex Propagation: Graph Convolutional Networks Based on Taylor Approximation
Songyang Zhang
Han Zhang
Shuguang Cui
Zhi Ding
GNN
36
1
0
01 Jul 2020
SCE: Scalable Network Embedding from Sparsest Cut
SCE: Scalable Network Embedding from Sparsest Cut
Shengzhong Zhang
Zengfeng Huang
Haicang Zhou
Ziang Zhou
SSL
BDL
29
18
0
30 Jun 2020
Path Integral Based Convolution and Pooling for Graph Neural Networks
Path Integral Based Convolution and Pooling for Graph Neural Networks
Zheng Ma
Junyu Xuan
Yu Guang Wang
Ming Li
Pietro Lio
GNN
39
54
0
29 Jun 2020
A Multiscale Graph Convolutional Network Using Hierarchical Clustering
A Multiscale Graph Convolutional Network Using Hierarchical Clustering
Alex Lipov
Pietro Lio
6
2
0
22 Jun 2020
Multipole Graph Neural Operator for Parametric Partial Differential
  Equations
Multipole Graph Neural Operator for Parametric Partial Differential Equations
Zong-Yi Li
Nikola B. Kovachki
Kamyar Azizzadenesheli
Burigede Liu
K. Bhattacharya
Andrew M. Stuart
Anima Anandkumar
AI4CE
24
377
0
16 Jun 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
37
31
0
15 Jun 2020
The Impact of Global Structural Information in Graph Neural Networks
  Applications
The Impact of Global Structural Information in Graph Neural Networks Applications
Davide Buffelli
Fabio Vandin
AI4CE
36
8
0
06 Jun 2020
Joint Item Recommendation and Attribute Inference: An Adaptive Graph
  Convolutional Network Approach
Joint Item Recommendation and Attribute Inference: An Adaptive Graph Convolutional Network Approach
Le Wu
Yonghui Yang
Kun Zhang
Richang Hong
Yanjie Fu
Meng Wang
GNN
11
101
0
25 May 2020
Graph Random Neural Network for Semi-Supervised Learning on Graphs
Graph Random Neural Network for Semi-Supervised Learning on Graphs
Wenzheng Feng
Jie Zhang
Yuxiao Dong
Yu Han
Huanbo Luan
Qian Xu
Qiang Yang
Evgeny Kharlamov
Jie Tang
28
387
0
22 May 2020
ENT-DESC: Entity Description Generation by Exploring Knowledge Graph
ENT-DESC: Entity Description Generation by Exploring Knowledge Graph
Liying Cheng
Dekun Wu
Lidong Bing
Yan Zhang
Zhanming Jie
Wei Lu
Luo Si
3DV
24
2
0
30 Apr 2020
Directed Graph Convolutional Network
Directed Graph Convolutional Network
Zekun Tong
Keli Zhang
Changsheng Sun
David S. Rosenblum
A. Lim
BDL
GNN
26
113
0
29 Apr 2020
Perturb More, Trap More: Understanding Behaviors of Graph Neural
  Networks
Perturb More, Trap More: Understanding Behaviors of Graph Neural Networks
Chaojie Ji
Ruxin Wang
Hongyan Wu
31
7
0
21 Apr 2020
L$^2$-GCN: Layer-Wise and Learned Efficient Training of Graph
  Convolutional Networks
L2^22-GCN: Layer-Wise and Learned Efficient Training of Graph Convolutional Networks
Yuning You
Tianlong Chen
Zhangyang Wang
Yang Shen
GNN
101
82
0
30 Mar 2020
Progressive Graph Convolutional Networks for Semi-Supervised Node
  Classification
Progressive Graph Convolutional Networks for Semi-Supervised Node Classification
Negar Heidari
Alexandros Iosifidis
GNN
29
14
0
27 Mar 2020
An Uncoupled Training Architecture for Large Graph Learning
An Uncoupled Training Architecture for Large Graph Learning
Dalong Yang
Chuan Chen
Youhao Zheng
Zibin Zheng
Shih-wei Liao
GNN
20
1
0
21 Mar 2020
Towards Time-Aware Context-Aware Deep Trust Prediction in Online Social
  Networks
Towards Time-Aware Context-Aware Deep Trust Prediction in Online Social Networks
S. Ghafari
19
2
0
21 Mar 2020
Adaptive Propagation Graph Convolutional Network
Adaptive Propagation Graph Convolutional Network
Indro Spinelli
Simone Scardapane
A. Uncini
GNN
16
72
0
24 Feb 2020
Graph Prolongation Convolutional Networks: Explicitly Multiscale Machine
  Learning on Graphs with Applications to Modeling of Cytoskeleton
Graph Prolongation Convolutional Networks: Explicitly Multiscale Machine Learning on Graphs with Applications to Modeling of Cytoskeleton
Cory Braker Scott
E. Mjolsness
22
3
0
14 Feb 2020
Graph Inference Learning for Semi-supervised Classification
Graph Inference Learning for Semi-supervised Classification
Chunyan Xu
Zhen Cui
Xiaobin Hong
Tong Zhang
Jian Yang
Wei Liu
24
30
0
17 Jan 2020
Multi-Channel Graph Convolutional Networks
Multi-Channel Graph Convolutional Networks
Kaixiong Zhou
Qingquan Song
Xiao Shi Huang
Daochen Zha
Na Zou
Xia Hu
22
6
0
17 Dec 2019
A Hierarchy of Graph Neural Networks Based on Learnable Local Features
A Hierarchy of Graph Neural Networks Based on Learnable Local Features
M. Li
Meng Dong
Jiawei Zhou
Alexander M. Rush
AI4CE
GNN
36
7
0
13 Nov 2019
Constant Curvature Graph Convolutional Networks
Constant Curvature Graph Convolutional Networks
Gregor Bachmann
Gary Bécigneul
O. Ganea
GNN
27
133
0
12 Nov 2019
Pre-train and Learn: Preserve Global Information for Graph Neural
  Networks
Pre-train and Learn: Preserve Global Information for Graph Neural Networks
Danhao Zhu
Xinyu Dai
Jiajun Chen
21
23
0
27 Oct 2019
Topological based classification using graph convolutional networks
Topological based classification using graph convolutional networks
R. Abel
I. Benami
Y. Louzoun
GNN
19
5
0
26 Oct 2019
Rethinking Kernel Methods for Node Representation Learning on Graphs
Rethinking Kernel Methods for Node Representation Learning on Graphs
Yu Tian
Long Zhao
Xi Peng
Dimitris N. Metaxas
34
23
0
06 Oct 2019
AdaGCN: Adaboosting Graph Convolutional Networks into Deep Models
AdaGCN: Adaboosting Graph Convolutional Networks into Deep Models
Ke Sun
Zhanxing Zhu
Zhouchen Lin
GNN
33
80
0
14 Aug 2019
Fast Haar Transforms for Graph Neural Networks
Fast Haar Transforms for Graph Neural Networks
Ming Li
Zheng Ma
Yu Guang Wang
Xiaosheng Zhuang
33
74
0
10 Jul 2019
Power up! Robust Graph Convolutional Network via Graph Powering
Power up! Robust Graph Convolutional Network via Graph Powering
Ming Jin
Heng Chang
Wenwu Zhu
Somayeh Sojoudi
AAML
GNN
19
27
0
24 May 2019
MixHop: Higher-Order Graph Convolutional Architectures via Sparsified
  Neighborhood Mixing
MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing
Sami Abu-El-Haija
Bryan Perozzi
Amol Kapoor
N. Alipourfard
Kristina Lerman
Hrayr Harutyunyan
Greg Ver Steeg
Aram Galstyan
GNN
33
884
0
30 Apr 2019
PAN: Path Integral Based Convolution for Deep Graph Neural Networks
PAN: Path Integral Based Convolution for Deep Graph Neural Networks
Zheng Ma
Ming Li
Yuguang Wang
GNN
24
24
0
24 Apr 2019
Simplifying Graph Convolutional Networks
Simplifying Graph Convolutional Networks
Felix Wu
Tianyi Zhang
Amauri Souza
Christopher Fifty
Tao Yu
Kilian Q. Weinberger
GNN
56
3,109
0
19 Feb 2019
On Filter Size in Graph Convolutional Networks
On Filter Size in Graph Convolutional Networks
D. V. Tran
Nicoló Navarin
A. Sperduti
GNN
49
50
0
23 Nov 2018
Predict then Propagate: Graph Neural Networks meet Personalized PageRank
Predict then Propagate: Graph Neural Networks meet Personalized PageRank
Johannes Klicpera
Aleksandar Bojchevski
Stephan Günnemann
GNN
106
1,659
0
14 Oct 2018
Every Node Counts: Self-Ensembling Graph Convolutional Networks for
  Semi-Supervised Learning
Every Node Counts: Self-Ensembling Graph Convolutional Networks for Semi-Supervised Learning
Yawei Luo
T. Guan
Junqing Yu
Ping Liu
Yi Yang
SSL
GNN
32
32
0
26 Sep 2018
Higher-order Graph Convolutional Networks
Higher-order Graph Convolutional Networks
J. B. Lee
Ryan A. Rossi
Xiangnan Kong
Sungchul Kim
Eunyee Koh
Anup B. Rao
GNN
22
35
0
12 Sep 2018
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