ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1706.02216
  4. Cited By
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
SurfCon: Synonym Discovery on Privacy-Aware Clinical Data
SurfCon: Synonym Discovery on Privacy-Aware Clinical DataKnowledge Discovery and Data Mining (KDD), 2019
Zhen Wang
Xiang Yue
Soheil Moosavinasab
Yungui Huang
Simon M. Lin
Huan Sun
128
15
0
21 Jun 2019
Popularity Prediction on Social Platforms with Coupled Graph Neural
  Networks
Popularity Prediction on Social Platforms with Coupled Graph Neural NetworksWeb Search and Data Mining (WSDM), 2019
Qi Cao
Huawei Shen
Jinhua Gao
Bingzheng Wei
Xueqi Cheng
GNN
204
147
0
21 Jun 2019
Graph Star Net for Generalized Multi-Task Learning
Graph Star Net for Generalized Multi-Task Learning
H. Lu
Seth H. Huang
Tian Ye
Xiuyan Guo
GNN
133
46
0
21 Jun 2019
Placeto: Learning Generalizable Device Placement Algorithms for
  Distributed Machine Learning
Placeto: Learning Generalizable Device Placement Algorithms for Distributed Machine LearningNeural Information Processing Systems (NeurIPS), 2019
Ravichandra Addanki
S. Venkatakrishnan
Shreyan Gupta
Hongzi Mao
Mohammad Alizadeh
OODOffRL
174
71
0
20 Jun 2019
ANAE: Learning Node Context Representation for Attributed Network
  Embedding
ANAE: Learning Node Context Representation for Attributed Network Embedding
Keting Cen
Huawei Shen
Jinhua Gao
Qi Cao
Bingbing Xu
Xueqi Cheng
GNN
130
1
0
20 Jun 2019
Making Fast Graph-based Algorithms with Graph Metric Embeddings
Making Fast Graph-based Algorithms with Graph Metric EmbeddingsAnnual Meeting of the Association for Computational Linguistics (ACL), 2019
Andrey Kutuzov
M. Dorgham
Oleksiy Oliynyk
Chris Biemann
Sergey Petrakov
158
6
0
17 Jun 2019
Learning Correlated Latent Representations with Adaptive Priors
Learning Correlated Latent Representations with Adaptive Priors
Da Tang
Dawen Liang
Nicholas Ruozzi
Tony Jebara
BDLCML
275
1
0
14 Jun 2019
Identifying Illicit Accounts in Large Scale E-payment Networks -- A
  Graph Representation Learning Approach
Identifying Illicit Accounts in Large Scale E-payment Networks -- A Graph Representation Learning Approach
D. Tam
Wing Cheong Lau
Bin Hu
Qiufang Ying
D. Chiu
Hong Liu
GNN
158
24
0
13 Jun 2019
Utilizing Edge Features in Graph Neural Networks via Variational
  Information Maximization
Utilizing Edge Features in Graph Neural Networks via Variational Information Maximization
Pengfei Chen
Weiwen Liu
Chang-Yu Hsieh
Guangyong Chen
Shengyu Zhang
132
21
0
13 Jun 2019
Multiple instance learning with graph neural networks
Multiple instance learning with graph neural networks
Ming Tu
Jing Huang
Xiaodong He
Bowen Zhou
159
66
0
12 Jun 2019
Hierarchical Graph-to-Graph Translation for Molecules
Hierarchical Graph-to-Graph Translation for Molecules
Wengong Jin
Regina Barzilay
Tommi Jaakkola
155
16
0
11 Jun 2019
Position-aware Graph Neural Networks
Position-aware Graph Neural NetworksInternational Conference on Machine Learning (ICML), 2019
Jiaxuan You
Rex Ying
J. Leskovec
290
551
0
11 Jun 2019
Learning the Graphical Structure of Electronic Health Records with Graph
  Convolutional Transformer
Learning the Graphical Structure of Electronic Health Records with Graph Convolutional TransformerAAAI Conference on Artificial Intelligence (AAAI), 2019
Edward Choi
Zhen Xu
Yujia Li
Michael W. Dusenberry
Gerardo Flores
Yuan Xue
Andrew M. Dai
MedIm
218
271
0
11 Jun 2019
Attacking Graph Convolutional Networks via Rewiring
Attacking Graph Convolutional Networks via Rewiring
Yao Ma
Suhang Wang
Tyler Derr
Lingfei Wu
Shucheng Zhou
AAMLGNN
172
89
0
10 Jun 2019
Redundancy-Free Computation Graphs for Graph Neural Networks
Redundancy-Free Computation Graphs for Graph Neural Networks
Zhihao Jia
Sina Lin
Rex Ying
Jiaxuan You
J. Leskovec
Alexander Aiken
GNN
72
11
0
09 Jun 2019
Dynamic Network Embedding via Incremental Skip-gram with Negative
  Sampling
Dynamic Network Embedding via Incremental Skip-gram with Negative SamplingScience China Information Sciences (SCIS), 2019
Hao Peng
Jianxin Li
Haozheng Yan
Qiran Gong
Senzhang Wang
Lin Liu
Lihong Wang
Xiang Ren
190
33
0
09 Jun 2019
A Two-Step Graph Convolutional Decoder for Molecule Generation
A Two-Step Graph Convolutional Decoder for Molecule Generation
Xavier Bresson
T. Laurent
118
66
0
08 Jun 2019
Labeled Graph Generative Adversarial Networks
Labeled Graph Generative Adversarial Networks
Shuangfei Fan
Bert Huang
GAN
153
33
0
07 Jun 2019
Learning Representations of Graph Data -- A Survey
Learning Representations of Graph Data -- A Survey
Mital Kinderkhedia
GNN
153
13
0
07 Jun 2019
DEMO-Net: Degree-specific Graph Neural Networks for Node and Graph
  Classification
DEMO-Net: Degree-specific Graph Neural Networks for Node and Graph ClassificationKnowledge Discovery and Data Mining (KDD), 2019
Jun Wu
Jingrui He
Jiejun Xu
GNN
336
226
0
05 Jun 2019
Deep Q-Learning for Directed Acyclic Graph Generation
Deep Q-Learning for Directed Acyclic Graph Generation
Laura DÁrcy
P. Corcoran
Alun D. Preece
BDLGNN
83
5
0
05 Jun 2019
Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional
  Networks
Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional NetworksNeural Information Processing Systems (NeurIPS), 2019
Sitao Luan
Mingde Zhao
Xiao-Wen Chang
Doina Precup
GNN
271
168
0
05 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
241
14
0
05 Jun 2019
Variational Inference for Graph Convolutional Networks in the Absence of
  Graph Data and Adversarial Settings
Variational Inference for Graph Convolutional Networks in the Absence of Graph Data and Adversarial Settings
P. Elinas
Edwin V. Bonilla
Louis C. Tiao
BDLGNN
374
10
0
05 Jun 2019
Information Competing Process for Learning Diversified Representations
Information Competing Process for Learning Diversified RepresentationsNeural Information Processing Systems (NeurIPS), 2019
Jie Hu
Rongrong Ji
Shengchuan Zhang
Xiaoshuai Sun
QiXiang Ye
Chia-Wen Lin
Q. Tian
356
16
0
04 Jun 2019
Coherent Comment Generation for Chinese Articles with a
  Graph-to-Sequence Model
Coherent Comment Generation for Chinese Articles with a Graph-to-Sequence ModelAnnual Meeting of the Association for Computational Linguistics (ACL), 2019
Wei Li
Jingjing Xu
Yancheng He
Shengli Yan
Yunfang Wu
Xu Sun
160
49
0
04 Jun 2019
An Efficient Graph Convolutional Network Technique for the Travelling
  Salesman Problem
An Efficient Graph Convolutional Network Technique for the Travelling Salesman Problem
Chaitanya K. Joshi
T. Laurent
Xavier Bresson
GNN
333
423
0
04 Jun 2019
DANE: Domain Adaptive Network Embedding
DANE: Domain Adaptive Network EmbeddingInternational Joint Conference on Artificial Intelligence (IJCAI), 2019
Yizhou Zhang
Guojie Song
Lun Du
Shuwen Yang
Yilun Jin
OOD
199
87
0
03 Jun 2019
Sequential Scenario-Specific Meta Learner for Online Recommendation
Sequential Scenario-Specific Meta Learner for Online RecommendationKnowledge Discovery and Data Mining (KDD), 2019
Zhengxiao Du
Xiaowei Wang
Hongxia Yang
Jingren Zhou
Jie Tang
OffRLLRMCLL
144
127
0
02 Jun 2019
Graph WaveNet for Deep Spatial-Temporal Graph Modeling
Graph WaveNet for Deep Spatial-Temporal Graph ModelingInternational Joint Conference on Artificial Intelligence (IJCAI), 2019
Zonghan Wu
Shirui Pan
Guodong Long
Jing Jiang
Chengqi Zhang
GNNAI4TS
459
2,729
0
31 May 2019
End to end learning and optimization on graphs
End to end learning and optimization on graphsNeural Information Processing Systems (NeurIPS), 2019
Bryan Wilder
Eric Ewing
B. Dilkina
Milind Tambe
GNN
237
117
0
31 May 2019
Pre-Training Graph Neural Networks for Generic Structural Feature
  Extraction
Pre-Training Graph Neural Networks for Generic Structural Feature Extraction
Ziniu Hu
Changjun Fan
Ting-Li Chen
Kai-Wei Chang
Luke Huan
134
47
0
31 May 2019
Explainability Techniques for Graph Convolutional Networks
Explainability Techniques for Graph Convolutional NetworksInternational Conference on Machine Learning (ICML), 2019
Federico Baldassarre
Hossein Azizpour
GNNFAtt
283
313
0
31 May 2019
Discriminative structural graph classification
Discriminative structural graph classification
Younjoo Seo
Andreas Loukas
Nathanael Perraudin
163
19
0
31 May 2019
Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph
  Kernels
Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph KernelsNeural Information Processing Systems (NeurIPS), 2019
S. Du
Kangcheng Hou
Barnabás Póczós
Ruslan Salakhutdinov
Ruosong Wang
Keyulu Xu
342
298
0
30 May 2019
Graph Normalizing Flows
Graph Normalizing FlowsNeural Information Processing Systems (NeurIPS), 2019
Jenny Liu
Aviral Kumar
Jimmy Ba
J. Kiros
Kevin Swersky
BDLGNNAI4CE
209
175
0
30 May 2019
Quantifying the Alignment of Graph and Features in Deep Learning
Quantifying the Alignment of Graph and Features in Deep LearningIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2019
Yifan Qian
P. Expert
Tom Rieu
P. Panzarasa
Mauricio Barahona
99
19
0
30 May 2019
On the equivalence between graph isomorphism testing and function
  approximation with GNNs
On the equivalence between graph isomorphism testing and function approximation with GNNsNeural Information Processing Systems (NeurIPS), 2019
Zhengdao Chen
Soledad Villar
Lei Chen
Joan Bruna
267
305
0
29 May 2019
Strategies for Pre-training Graph Neural Networks
Strategies for Pre-training Graph Neural NetworksInternational Conference on Learning Representations (ICLR), 2019
Weihua Hu
Bowen Liu
Joseph Gomes
Marinka Zitnik
Abigail Z. Jacobs
Vijay S. Pande
J. Leskovec
SSLAI4CE
416
1,642
0
29 May 2019
Graph DNA: Deep Neighborhood Aware Graph Encoding for Collaborative
  Filtering
Graph DNA: Deep Neighborhood Aware Graph Encoding for Collaborative FilteringInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2019
Liwei Wu
Hsiang-Fu Yu
Nikhil S. Rao
James Sharpnack
Cho-Jui Hsieh
GNN
159
10
0
29 May 2019
Sublinear Update Time Randomized Algorithms for Dynamic Graph Regression
Sublinear Update Time Randomized Algorithms for Dynamic Graph RegressionApplied Mathematics and Computation (Appl. Math. Comput.), 2019
M. H. Chehreghani
214
1
0
28 May 2019
Cross-lingual Knowledge Graph Alignment via Graph Matching Neural
  Network
Cross-lingual Knowledge Graph Alignment via Graph Matching Neural NetworkAnnual Meeting of the Association for Computational Linguistics (ACL), 2019
Kun Xu
Liwei Wang
Mo Yu
Yansong Feng
Yan Song
Zhiguo Wang
Dong Yu
265
257
0
28 May 2019
Towards Interpretable Sparse Graph Representation Learning with
  Laplacian Pooling
Towards Interpretable Sparse Graph Representation Learning with Laplacian Pooling
Emmanuel Noutahi
Dominique Beaini
Julien Horwood
Sébastien Giguère
Prudencio Tossou
AI4CE
369
41
0
28 May 2019
Representation Learning for Dynamic Graphs: A Survey
Representation Learning for Dynamic Graphs: A SurveyJournal of machine learning research (JMLR), 2019
Seyed Mehran Kazemi
Rishab Goel
Kshitij Jain
I. Kobyzev
Akshay Sethi
Peter Forsyth
Pascal Poupart
AI4TSAI4CEGNN
307
539
0
27 May 2019
Incidence Networks for Geometric Deep Learning
Incidence Networks for Geometric Deep LearningInternational Conference on Machine Learning (ICML), 2019
Marjan Albooyeh
Daniele Bertolini
Siamak Ravanbakhsh
GNN
118
27
0
27 May 2019
STAR-GCN: Stacked and Reconstructed Graph Convolutional Networks for
  Recommender Systems
STAR-GCN: Stacked and Reconstructed Graph Convolutional Networks for Recommender SystemsInternational Joint Conference on Artificial Intelligence (IJCAI), 2019
Jiani Zhang
Xingjian Shi
Shenglin Zhao
Irwin King
131
253
0
27 May 2019
Provably Powerful Graph Networks
Provably Powerful Graph NetworksNeural Information Processing Systems (NeurIPS), 2019
Haggai Maron
Heli Ben-Hamu
Hadar Serviansky
Y. Lipman
506
636
0
27 May 2019
MCNE: An End-to-End Framework for Learning Multiple Conditional Network
  Representations of Social Network
MCNE: An End-to-End Framework for Learning Multiple Conditional Network Representations of Social NetworkKnowledge Discovery and Data Mining (KDD), 2019
Hao Wang
Tong Xu
Qi Liu
Defu Lian
Enhong Chen
Dongfang Du
Han Wu
Wen Su
151
126
0
27 May 2019
Graph Filtration Learning
Graph Filtration LearningInternational Conference on Machine Learning (ICML), 2019
Christoph Hofer
Florian Graf
Bastian Rieck
Marc Niethammer
Roland Kwitt
278
119
0
27 May 2019
Edge Contraction Pooling for Graph Neural Networks
Edge Contraction Pooling for Graph Neural Networks
Frederik Diehl
GNN
279
149
0
27 May 2019
Previous
123...119120121...124125126
Next