ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2111.10772
  4. Cited By
Network representation learning: A macro and micro view

Network representation learning: A macro and micro view

21 November 2021
Xueyi Liu
Jie Tang
    GNNAI4TS
ArXiv (abs)PDFHTML

Papers citing "Network representation learning: A macro and micro view"

50 / 85 papers shown
Title
Generative Adversarial Networks
Generative Adversarial Networks
Gilad Cohen
Raja Giryes
GAN
283
30,149
0
01 Mar 2022
GPT-GNN: Generative Pre-Training of Graph Neural Networks
GPT-GNN: Generative Pre-Training of Graph Neural Networks
Ziniu Hu
Yuxiao Dong
Kuansan Wang
Kai-Wei Chang
Yizhou Sun
SSLAI4CE
158
563
0
27 Jun 2020
Self-supervised Learning on Graphs: Deep Insights and New Direction
Self-supervised Learning on Graphs: Deep Insights and New Direction
Wei Jin
Hanyu Wang
Haochen Liu
Yiqi Wang
Suhang Wang
Zitao Liu
Jiliang Tang
SSL
60
178
0
17 Jun 2020
GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training
GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training
J. Qiu
Qibin Chen
Yuxiao Dong
Jing Zhang
Hongxia Yang
Ming Ding
Kuansan Wang
Jie Tang
SSL
226
959
0
17 Jun 2020
Rethinking Pre-training and Self-training
Rethinking Pre-training and Self-training
Barret Zoph
Golnaz Ghiasi
Nayeon Lee
Huayu Chen
Hanxiao Liu
E. D. Cubuk
Quoc V. Le
SSeg
96
652
0
11 Jun 2020
Self-supervised Training of Graph Convolutional Networks
Self-supervised Training of Graph Convolutional Networks
Qikui Zhu
Bo Du
Pingkun Yan
SSLGNN
52
45
0
03 Jun 2020
Beyond Accuracy: Behavioral Testing of NLP models with CheckList
Beyond Accuracy: Behavioral Testing of NLP models with CheckList
Marco Tulio Ribeiro
Tongshuang Wu
Carlos Guestrin
Sameer Singh
ELM
208
1,107
0
08 May 2020
Heterogeneous Network Representation Learning: A Unified Framework with
  Survey and Benchmark
Heterogeneous Network Representation Learning: A Unified Framework with Survey and Benchmark
Carl Yang
Yuxin Xiao
Yu Zhang
Yizhou Sun
Jiawei Han
AI4TS
113
58
0
01 Apr 2020
Designing Network Design Spaces
Designing Network Design Spaces
Ilija Radosavovic
Raj Prateek Kosaraju
Ross B. Girshick
Kaiming He
Piotr Dollár
GNN
102
1,691
0
30 Mar 2020
Self-Supervised Graph Representation Learning via Global Context
  Prediction
Self-Supervised Graph Representation Learning via Global Context Prediction
Zhen Peng
Yixiang Dong
Minnan Luo
Xiao-Ming Wu
Q. Zheng
SSL
82
65
0
03 Mar 2020
Heterogeneous Graph Transformer
Heterogeneous Graph Transformer
Ziniu Hu
Yuxiao Dong
Kuansan Wang
Yizhou Sun
284
1,208
0
03 Mar 2020
A Simple Framework for Contrastive Learning of Visual Representations
A Simple Framework for Contrastive Learning of Visual Representations
Ting-Li Chen
Simon Kornblith
Mohammad Norouzi
Geoffrey E. Hinton
SSL
375
18,859
0
13 Feb 2020
GraphAF: a Flow-based Autoregressive Model for Molecular Graph
  Generation
GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation
Chence Shi
Minkai Xu
Zhaocheng Zhu
Weinan Zhang
Ming Zhang
Jian Tang
173
438
0
26 Jan 2020
Fast Sequence-Based Embedding with Diffusion Graphs
Fast Sequence-Based Embedding with Diffusion Graphs
Benedek Rozemberczki
Rik Sarkar
GNN
43
61
0
21 Jan 2020
Graph-Bert: Only Attention is Needed for Learning Graph Representations
Graph-Bert: Only Attention is Needed for Learning Graph Representations
Jiawei Zhang
Haopeng Zhang
Congying Xia
Li Sun
86
305
0
15 Jan 2020
An Attention-based Graph Neural Network for Heterogeneous Structural
  Learning
An Attention-based Graph Neural Network for Heterogeneous Structural Learning
Huiting Hong
Hantao Guo
Yucheng Lin
Xiaoqing Yang
Zang Li
Jieping Ye
58
219
0
19 Dec 2019
GraLSP: Graph Neural Networks with Local Structural Patterns
GraLSP: Graph Neural Networks with Local Structural Patterns
Yilun Jin
Guojie Song
C. Shi
71
52
0
18 Nov 2019
Momentum Contrast for Unsupervised Visual Representation Learning
Momentum Contrast for Unsupervised Visual Representation Learning
Kaiming He
Haoqi Fan
Yuxin Wu
Saining Xie
Ross B. Girshick
SSL
207
12,121
0
13 Nov 2019
Neural Execution of Graph Algorithms
Neural Execution of Graph Algorithms
Petar Velickovic
Rex Ying
Matilde Padovano
R. Hadsell
Charles Blundell
GNN
85
171
0
23 Oct 2019
GraphZoom: A multi-level spectral approach for accurate and scalable
  graph embedding
GraphZoom: A multi-level spectral approach for accurate and scalable graph embedding
Chenhui Deng
Zhiqiang Zhao
Yongyu Wang
Zhiru Zhang
Zhuo Feng
66
106
0
06 Oct 2019
PairNorm: Tackling Oversmoothing in GNNs
PairNorm: Tackling Oversmoothing in GNNs
Lingxiao Zhao
Leman Akoglu
71
509
0
26 Sep 2019
GraphMix: Improved Training of GNNs for Semi-Supervised Learning
GraphMix: Improved Training of GNNs for Semi-Supervised Learning
Vikas Verma
Meng Qu
Kenji Kawaguchi
Alex Lamb
Yoshua Bengio
Arno Solin
Jian Tang
63
62
0
25 Sep 2019
HeteSpaceyWalk: A Heterogeneous Spacey Random Walk for Heterogeneous
  Information Network Embedding
HeteSpaceyWalk: A Heterogeneous Spacey Random Walk for Heterogeneous Information Network Embedding
Yu He
Yangqiu Song
Jianxin Li
Cheng Ji
Jian Peng
Hao Peng
75
112
0
07 Sep 2019
Measuring and Relieving the Over-smoothing Problem for Graph Neural
  Networks from the Topological View
Measuring and Relieving the Over-smoothing Problem for Graph Neural Networks from the Topological View
Deli Chen
Yankai Lin
Wei Li
Peng Li
Jie Zhou
Xu Sun
92
1,112
0
07 Sep 2019
Auto-GNN: Neural Architecture Search of Graph Neural Networks
Auto-GNN: Neural Architecture Search of Graph Neural Networks
Kaixiong Zhou
Qingquan Song
Xiao Huang
Xia Hu
GNN
104
182
0
07 Sep 2019
InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation
  Learning via Mutual Information Maximization
InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization
Fan-Yun Sun
Jordan Hoffmann
Vikas Verma
Jian Tang
SSL
153
864
0
31 Jul 2019
DropEdge: Towards Deep Graph Convolutional Networks on Node
  Classification
DropEdge: Towards Deep Graph Convolutional Networks on Node Classification
Yu Rong
Wenbing Huang
Tingyang Xu
Junzhou Huang
110
1,343
0
25 Jul 2019
GraphSAINT: Graph Sampling Based Inductive Learning Method
GraphSAINT: Graph Sampling Based Inductive Learning Method
Hanqing Zeng
Hongkuan Zhou
Ajitesh Srivastava
Rajgopal Kannan
Viktor Prasanna
GNN
137
968
0
10 Jul 2019
NetSMF: Large-Scale Network Embedding as Sparse Matrix Factorization
NetSMF: Large-Scale Network Embedding as Sparse Matrix Factorization
J. Qiu
Yuxiao Dong
Hao Ma
Jun Yu Li
Chi Wang
Kuansan Wang
Jie Tang
54
173
0
26 Jun 2019
AGAN: Towards Automated Design of Generative Adversarial Networks
AGAN: Towards Automated Design of Generative Adversarial Networks
Hanchao Wang
Jun Huan
GANAI4CE
41
37
0
25 Jun 2019
Can Graph Neural Networks Help Logic Reasoning?
Can Graph Neural Networks Help Logic Reasoning?
Yuyu Zhang
Xinshi Chen
Yu’an Yang
Arun Ramamurthy
Bo Li
Yuan Qi
Le Song
NAIAI4CE
50
13
0
05 Jun 2019
On Network Design Spaces for Visual Recognition
On Network Design Spaces for Visual Recognition
Ilija Radosavovic
Justin Johnson
Saining Xie
Wan-Yen Lo
Piotr Dollár
83
135
0
30 May 2019
What Can Neural Networks Reason About?
What Can Neural Networks Reason About?
Keyulu Xu
Jingling Li
Mozhi Zhang
S. Du
Ken-ichi Kawarabayashi
Stefanie Jegelka
NAIAI4CE
73
246
0
30 May 2019
Strategies for Pre-training Graph Neural Networks
Strategies for Pre-training Graph Neural Networks
Weihua Hu
Bowen Liu
Joseph Gomes
Marinka Zitnik
Percy Liang
Vijay S. Pande
J. Leskovec
SSLAI4CE
116
1,409
0
29 May 2019
Revisiting Graph Neural Networks: All We Have is Low-Pass Filters
Revisiting Graph Neural Networks: All We Have is Low-Pass Filters
Hoang NT
Takanori Maehara
GNN
124
434
0
23 May 2019
GMNN: Graph Markov Neural Networks
GMNN: Graph Markov Neural Networks
Meng Qu
Yoshua Bengio
Jian Tang
BDLGNN
67
292
0
15 May 2019
Representation Learning for Attributed Multiplex Heterogeneous Network
Representation Learning for Attributed Multiplex Heterogeneous Network
Yukuo Cen
Xu Zou
Jianwei Zhang
Hongxia Yang
Jingren Zhou
Jie Tang
GNN
65
435
0
05 May 2019
Graph Wavelet Neural Network
Graph Wavelet Neural Network
Bingbing Xu
Huawei Shen
Qi Cao
Yunqi Qiu
Xueqi Cheng
GNN
70
332
0
12 Apr 2019
Single Path One-Shot Neural Architecture Search with Uniform Sampling
Single Path One-Shot Neural Architecture Search with Uniform Sampling
Zichao Guo
Xiangyu Zhang
Haoyuan Mu
Wen Heng
Zechun Liu
Yichen Wei
Jian Sun
96
939
0
31 Mar 2019
Batch Virtual Adversarial Training for Graph Convolutional Networks
Batch Virtual Adversarial Training for Graph Convolutional Networks
Zhijie Deng
Yinpeng Dong
Jun Zhu
GNN
73
63
0
25 Feb 2019
Simplifying Graph Convolutional Networks
Simplifying Graph Convolutional Networks
Felix Wu
Tianyi Zhang
Amauri Souza
Christopher Fifty
Tao Yu
Kilian Q. Weinberger
GNN
244
3,179
0
19 Feb 2019
Adversarial Attack and Defense on Graph Data: A Survey
Adversarial Attack and Defense on Graph Data: A Survey
Lichao Sun
Yingtong Dou
Carl Yang
Ji Wang
Yixin Liu
Philip S. Yu
Lifang He
Yangqiu Song
GNNAAML
74
283
0
26 Dec 2018
Fast Randomized PCA for Sparse Data
Fast Randomized PCA for Sparse Data
Xu Feng
Yuyang Xie
Mingye Song
Wenjian Yu
Jie Tang
57
30
0
16 Oct 2018
How Powerful are Graph Neural Networks?
How Powerful are Graph Neural Networks?
Keyulu Xu
Weihua Hu
J. Leskovec
Stefanie Jegelka
GNN
245
7,681
0
01 Oct 2018
Deep Graph Infomax
Deep Graph Infomax
Petar Velickovic
W. Fedus
William L. Hamilton
Pietro Lio
Yoshua Bengio
R. Devon Hjelm
GNN
130
2,396
0
27 Sep 2018
Adaptive Sampling Towards Fast Graph Representation Learning
Adaptive Sampling Towards Fast Graph Representation Learning
Wen-bing Huang
Tong Zhang
Yu Rong
Junzhou Huang
GNN
77
491
0
14 Sep 2018
Adversarial Attacks on Node Embeddings via Graph Poisoning
Adversarial Attacks on Node Embeddings via Graph Poisoning
Aleksandar Bojchevski
Stephan Günnemann
AAML
65
307
0
04 Sep 2018
Graph Convolutional Policy Network for Goal-Directed Molecular Graph
  Generation
Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation
Jiaxuan You
Bowen Liu
Rex Ying
Vijay S. Pande
J. Leskovec
GNN
295
902
0
07 Jun 2018
Adversarial Attacks on Neural Networks for Graph Data
Adversarial Attacks on Neural Networks for Graph Data
Daniel Zügner
Amir Akbarnejad
Stephan Günnemann
GNNAAMLOOD
159
1,070
0
21 May 2018
Attention-based Graph Neural Network for Semi-supervised Learning
Attention-based Graph Neural Network for Semi-supervised Learning
K. K. Thekumparampil
Chong-Jun Wang
Sewoong Oh
Li Li
GNN
76
333
0
10 Mar 2018
12
Next