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Inductive Representation Learning on Large Graphs
v1v2v3v4 (latest)

Inductive Representation Learning on Large Graphs

Neural Information Processing Systems (NeurIPS), 2017
7 June 2017
William L. Hamilton
Z. Ying
J. Leskovec
ArXiv (abs)PDFHTML

Papers citing "Inductive Representation Learning on Large Graphs"

50 / 6,280 papers shown
Graph Neural Networks Exponentially Lose Expressive Power for Node
  Classification
Graph Neural Networks Exponentially Lose Expressive Power for Node Classification
Kenta Oono
Taiji Suzuki
GNN
327
30
0
27 May 2019
Optimizing Generalized PageRank Methods for Seed-Expansion Community
  Detection
Optimizing Generalized PageRank Methods for Seed-Expansion Community DetectionNeural Information Processing Systems (NeurIPS), 2019
Pan Li
Eli Chien
O. Milenkovic
323
72
0
26 May 2019
A Flexible Generative Framework for Graph-based Semi-supervised Learning
A Flexible Generative Framework for Graph-based Semi-supervised LearningNeural Information Processing Systems (NeurIPS), 2019
Jiaqi Ma
Weijing Tang
Ji Zhu
Qiaozhu Mei
BDL
191
68
0
26 May 2019
Graph Attention Auto-Encoders
Graph Attention Auto-EncodersIEEE International Conference on Tools with Artificial Intelligence (ICTAI), 2019
Amin Salehi
H. Davulcu
GNN
97
153
0
26 May 2019
Demand Forecasting from Spatiotemporal Data with Graph Networks and
  Temporal-Guided Embedding
Demand Forecasting from Spatiotemporal Data with Graph Networks and Temporal-Guided Embedding
Doyup Lee
Suehun Jung
Yeongjae Cheon
Dongil Kim
Seungil You
AI4TS
135
6
0
26 May 2019
Compositional Fairness Constraints for Graph Embeddings
Compositional Fairness Constraints for Graph EmbeddingsInternational Conference on Machine Learning (ICML), 2019
A. Bose
William L. Hamilton
FaML
314
282
0
25 May 2019
Is a Single Vector Enough? Exploring Node Polysemy for Network Embedding
Is a Single Vector Enough? Exploring Node Polysemy for Network EmbeddingKnowledge Discovery and Data Mining (KDD), 2019
Ninghao Liu
Qiaoyu Tan
Yuening Li
Hongxia Yang
Jingren Zhou
Helen Zhou
156
89
0
25 May 2019
Learning to Identify High Betweenness Centrality Nodes from Scratch: A
  Novel Graph Neural Network Approach
Learning to Identify High Betweenness Centrality Nodes from Scratch: A Novel Graph Neural Network ApproachInternational Conference on Information and Knowledge Management (CIKM), 2019
Changjun Fan
Li Zeng
Yuhui Ding
Muhao Chen
Luke Huan
Zhong Liu
GNN
248
74
0
24 May 2019
Approximation Ratios of Graph Neural Networks for Combinatorial Problems
Approximation Ratios of Graph Neural Networks for Combinatorial ProblemsNeural Information Processing Systems (NeurIPS), 2019
Ryoma Sato
M. Yamada
H. Kashima
GNN
349
137
0
24 May 2019
Low-dimensional statistical manifold embedding of directed graphs
Low-dimensional statistical manifold embedding of directed graphsInternational Conference on Learning Representations (ICLR), 2019
Thorben Funke
Tian Guo
Alen Lancic
Nino Antulov-Fantulin
276
5
0
24 May 2019
Learning Cross-Domain Representation with Multi-Graph Neural Network
Learning Cross-Domain Representation with Multi-Graph Neural Network
Ouyang Yi
Bin Guo
Xing Tang
Xiuqiang He
Jian Xiong
Zhiwen Yu
AI4CE
90
22
0
24 May 2019
Power up! Robust Graph Convolutional Network via Graph Powering
Power up! Robust Graph Convolutional Network via Graph PoweringAAAI Conference on Artificial Intelligence (AAAI), 2019
Ming Jin
Heng Chang
Wenwu Zhu
Somayeh Sojoudi
AAMLGNN
302
28
0
24 May 2019
Meta-GNN: On Few-shot Node Classification in Graph Meta-learning
Meta-GNN: On Few-shot Node Classification in Graph Meta-learningInternational Conference on Information and Knowledge Management (CIKM), 2019
Fan Zhou
Chengtai Cao
Kunpeng Zhang
Goce Trajcevski
Ting Zhong
Ji Geng
167
264
0
23 May 2019
MR-GNN: Multi-Resolution and Dual Graph Neural Network for Predicting
  Structured Entity Interactions
MR-GNN: Multi-Resolution and Dual Graph Neural Network for Predicting Structured Entity InteractionsInternational Joint Conference on Artificial Intelligence (IJCAI), 2019
Nuo Xu
Peijie Wang
Long Chen
Jing Tao
Junzhou Zhao
GNN
127
113
0
23 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
460
493
0
23 May 2019
Estimating Node Importance in Knowledge Graphs Using Graph Neural
  Networks
Estimating Node Importance in Knowledge Graphs Using Graph Neural NetworksKnowledge Discovery and Data Mining (KDD), 2019
Namyong Park
Andrey Kan
Xin Luna Dong
Tong Zhao
Christos Faloutsos
209
171
0
21 May 2019
Joint embedding of structure and features via graph convolutional
  networks
Joint embedding of structure and features via graph convolutional networksApplied Network Science (Appl Netw Sci), 2019
Sébastien Lerique
Jacob Levy Abitbol
M. Karsai
GNN
219
33
0
21 May 2019
Marginalized Average Attentional Network for Weakly-Supervised Learning
Marginalized Average Attentional Network for Weakly-Supervised LearningInternational Conference on Learning Representations (ICLR), 2019
Yuan. Yuan
Yueming Lyu
Xi Shen
Ivor W. Tsang
Dit-Yan Yeung
165
83
0
21 May 2019
Mutual Information Maximization in Graph Neural Networks
Mutual Information Maximization in Graph Neural NetworksIEEE International Joint Conference on Neural Network (IJCNN), 2019
Xinhan Di
Pengqian Yu
Rui Bu
Mingchao Sun
285
24
0
21 May 2019
Neural Graph Collaborative Filtering
Neural Graph Collaborative FilteringAnnual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2019
Xiang Wang
Xiangnan He
Meng Wang
Fuli Feng
Tat-Seng Chua
387
3,473
0
20 May 2019
Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph
  Convolutional Networks
Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional NetworksKnowledge Discovery and Data Mining (KDD), 2019
Wei-Lin Chiang
Xuanqing Liu
Si Si
Yang Li
Samy Bengio
Cho-Jui Hsieh
GNN
364
1,456
0
20 May 2019
KGAT: Knowledge Graph Attention Network for Recommendation
KGAT: Knowledge Graph Attention Network for RecommendationKnowledge Discovery and Data Mining (KDD), 2019
Xiang Wang
Xiangnan He
Yixin Cao
Meng Liu
Tat-Seng Chua
OffRL
274
2,076
0
20 May 2019
Multi-hop Reading Comprehension across Multiple Documents by Reasoning
  over Heterogeneous Graphs
Multi-hop Reading Comprehension across Multiple Documents by Reasoning over Heterogeneous GraphsAnnual Meeting of the Association for Computational Linguistics (ACL), 2019
Ming Tu
Guangtao Wang
Jing-ling Huang
Yun Tang
Xiaodong He
Bowen Zhou
229
158
0
17 May 2019
Function Space Pooling For Graph Convolutional Networks
Function Space Pooling For Graph Convolutional NetworksInternational Cross-Domain Conference on Machine Learning and Knowledge Extraction (CD-MAKE), 2019
P. Corcoran
GNN
261
3
0
15 May 2019
GMNN: Graph Markov Neural Networks
GMNN: Graph Markov Neural NetworksInternational Conference on Machine Learning (ICML), 2019
Meng Qu
Yoshua Bengio
Jian Tang
BDLGNN
320
314
0
15 May 2019
Embeddings and Representation Learning for Structured Data
Embeddings and Representation Learning for Structured DataThe European Symposium on Artificial Neural Networks (ESANN), 2019
Benjamin Paassen
Claudio Gallicchio
Alessio Micheli
A. Sperduti
129
7
0
15 May 2019
Can Graph Neural Networks Go "Online"? An Analysis of Pretraining and
  Inference
Can Graph Neural Networks Go "Online"? An Analysis of Pretraining and Inference
Lukas Galke
Iacopo Vagliano
A. Scherp
CLLGNNOnRLAI4CE
120
10
0
15 May 2019
Stochastic Blockmodels meet Graph Neural Networks
Stochastic Blockmodels meet Graph Neural NetworksInternational Conference on Machine Learning (ICML), 2019
Nikhil Mehta
Lawrence Carin
Piyush Rai
BDL
158
89
0
14 May 2019
Multi-scale Dynamic Graph Convolutional Network for Hyperspectral Image
  Classification
Multi-scale Dynamic Graph Convolutional Network for Hyperspectral Image ClassificationIEEE Transactions on Geoscience and Remote Sensing (TGRS), 2019
Sheng Wan
Chen Gong
P. Zhong
Bo Du
Lefei Zhang
Zhiqiang Wang
135
420
0
14 May 2019
Correlated Variational Auto-Encoders
Correlated Variational Auto-EncodersInternational Conference on Machine Learning (ICML), 2019
Da Tang
Dawen Liang
Tony Jebara
Nicholas Ruozzi
CMLGNN
259
21
0
14 May 2019
Hierarchically Structured Meta-learning
Hierarchically Structured Meta-learningInternational Conference on Machine Learning (ICML), 2019
Huaxiu Yao
Ying Wei
Junzhou Huang
Ruoyao Xiao
192
218
0
13 May 2019
Can NetGAN be improved on short random walks?
Can NetGAN be improved on short random walks?Brazilian Conference on Intelligent Systems (BRACIS), 2019
Amir Jalilifard
Vinicius Fernandes Caridá
Alex F. Mansano
Rogers Cristo
71
3
0
13 May 2019
Craquelure as a Graph: Application of Image Processing and Graph Neural
  Networks to the Description of Fracture Patterns
Craquelure as a Graph: Application of Image Processing and Graph Neural Networks to the Description of Fracture Patterns
Oleksii Sidorov
J. Hardeberg
118
6
0
13 May 2019
On Graph Classification Networks, Datasets and Baselines
On Graph Classification Networks, Datasets and Baselines
Enxhell Luzhnica
Ben Day
Pietro Lio
GNN
119
19
0
12 May 2019
Language in Our Time: An Empirical Analysis of Hashtags
Language in Our Time: An Empirical Analysis of HashtagsThe Web Conference (WWW), 2019
Yang Zhang
219
27
0
11 May 2019
Are Powerful Graph Neural Nets Necessary? A Dissection on Graph
  Classification
Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification
Ting-Li Chen
Song Bian
Luke Huan
215
99
0
11 May 2019
Graph U-Nets
Graph U-NetsIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2019
Hongyang Gao
Shuiwang Ji
AI4CESSLSSegGNN
560
1,207
0
11 May 2019
Knowledge-aware Graph Neural Networks with Label Smoothness
  Regularization for Recommender Systems
Knowledge-aware Graph Neural Networks with Label Smoothness Regularization for Recommender SystemsKnowledge Discovery and Data Mining (KDD), 2019
Hongwei Wang
Fuzheng Zhang
Mengdi Zhang
J. Leskovec
Miao Zhao
Wenjie Li
Zhongyuan Wang
237
617
0
11 May 2019
Prototype Propagation Networks (PPN) for Weakly-supervised Few-shot
  Learning on Category Graph
Prototype Propagation Networks (PPN) for Weakly-supervised Few-shot Learning on Category GraphInternational Joint Conference on Artificial Intelligence (IJCAI), 2019
Lu Liu
Wanrong Zhu
Guodong Long
Jing Jiang
Lina Yao
Chengqi Zhang
217
73
0
10 May 2019
Adversarial Defense Framework for Graph Neural Network
Adversarial Defense Framework for Graph Neural Network
Shen Wang
Zhengzhang Chen
Jingchao Ni
Xiao Yu
Zhichun Li
Haifeng Chen
Philip S. Yu
AAMLGNN
149
30
0
09 May 2019
Multi-modal Graph Fusion for Inductive Disease Classification in
  Incomplete Datasets
Multi-modal Graph Fusion for Inductive Disease Classification in Incomplete Datasets
G. Vivar
Hendrik Burwinkel
Anees Kazi
A. Zwergal
Nassir Navab
Seyed-Ahmad Ahmadi
143
4
0
08 May 2019
PiNet: A Permutation Invariant Graph Neural Network for Graph
  Classification
PiNet: A Permutation Invariant Graph Neural Network for Graph Classification
Peter Meltzer
Marcelo Daniel Gutierrez Mallea
Peter J Bentley
GNN
140
12
0
08 May 2019
Adaptive Image-Feature Learning for Disease Classification Using
  Inductive Graph Networks
Adaptive Image-Feature Learning for Disease Classification Using Inductive Graph NetworksInternational Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2019
Hendrik Burwinkel
Anees Kazi
G. Vivar
Shadi Albarqouni
G. Zahnd
Nassir Navab
Seyed-Ahmad Ahmadi
AI4CE
153
15
0
08 May 2019
Representation Learning for Attributed Multiplex Heterogeneous Network
Representation Learning for Attributed Multiplex Heterogeneous NetworkKnowledge Discovery and Data Mining (KDD), 2019
Yukuo Cen
Xu Zou
Jianwei Zhang
Hongxia Yang
Jingren Zhou
Jie Tang
GNN
193
453
0
05 May 2019
Learning Graph Neural Networks with Noisy Labels
Learning Graph Neural Networks with Noisy Labels
Hoang NT
C. J. Jin
T. Murata
NoLa
108
54
0
05 May 2019
Edge-labeling Graph Neural Network for Few-shot Learning
Edge-labeling Graph Neural Network for Few-shot LearningComputer Vision and Pattern Recognition (CVPR), 2019
Jongmin Kim
Taesup Kim
Sungwoong Kim
Chang D. Yoo
205
505
0
04 May 2019
Temporal Graph Convolutional Networks for Automatic Seizure Detection
Temporal Graph Convolutional Networks for Automatic Seizure DetectionMachine Learning in Health Care (MLHC), 2019
Ian Covert
B. Krishnan
I. Najm
Jiening Zhan
Matthew Shore
J. Hixson
M. Po
148
86
0
03 May 2019
Stability and Generalization of Graph Convolutional Neural Networks
Stability and Generalization of Graph Convolutional Neural NetworksKnowledge Discovery and Data Mining (KDD), 2019
Saurabh Verma
Zhi-Li Zhang
GNNMLT
343
176
0
03 May 2019
On the Use of ArXiv as a Dataset
On the Use of ArXiv as a Dataset
Colin B. Clement
Matthew Bierbaum
K. O’Keeffe
Alexander A. Alemi
AI4CE
541
165
0
30 Apr 2019
Graph Convolutional Networks with EigenPooling
Graph Convolutional Networks with EigenPoolingKnowledge Discovery and Data Mining (KDD), 2019
Yao Ma
Suhang Wang
Charu C. Aggarwal
Shucheng Zhou
GNN
354
351
0
30 Apr 2019
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