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Learning latent representations of nodes in graphs is an important and ubiquitous task with widespread applications such as link prediction, node classification, and graph visualization.
A global geometric framework for nonlinear dimensionality reduction
Joshua B Tenenbaum, Vin De Silva, and John C Langford · 2000
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Laplacian eigenmaps and spectral techniques for embedding and clustering
Mikhail Belkin and Partha Niyogi · 2001
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Introducing the enron corpus
Bryan Klimt and Yiming Yang · 2004
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Empirical analysis of an evolving social network
Gueorgi Kossinets and Duncan J Watts · 2006
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Graph evolution: Densification and shrinking diameters
Jure Leskovec, Jon Kleinberg, and Christos Faloutsos · 2007
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Patterns and dynamics of users’ behavior and interaction: Network analysis of an online community
Pietro Panzarasa, Tore Opsahl, and Kathleen M. Carley · 2009
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Deepwalk: online learning of social representations
Bryan Perozzi, Rami Al-Rfou, and Steven Skiena · 2014
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Dropout: a simple way to prevent neural networks from overfitting
Nitish Srivastava, Geoffrey E. Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov · 2014
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Knowledge graph embedding by translating on hyperplanes
Zhen Wang, Jianwen Zhang, Jianlin Feng, and Zheng Chen · 2014
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Neural machine translation by jointly learning to align and translate
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio · 2015
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2015
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LINE: large-scale information network embedding
Jian Tang, Meng Qu, Mingzhe Wang, Ming Zhang, Jun Yan, and Qiaozhu Mei · 2015
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Tensorflow: A system for large-scale machine learning
Martín Abadi, Paul Barham, Jianmin Chen, Zhifeng Chen, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Geoffrey Irving, Michael Isard, Manjunath Kudlur, Josh Levenberg, Rajat Monga, Sherry Moore, Derek Gordon Murray, Benoit Steiner, Paul A. Tucker, Vijay Vasudevan, Pete Warden, Martin Wicke, Yuan Yu, and Xiaoqiang Zheng · 2016
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Convolutional neural networks on graphs with fast localized spectral filtering
Michaël Defferrard, Xavier Bresson, and Pierre Vandergheynst · 2016
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node2vec: Scalable feature learning for networks
Aditya Grover and Jure Leskovec · 2016
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The movielens datasets: History and context
F Maxwell Harper and Joseph A Konstan · 2016
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Learning convolutional neural networks for graphs
Mathias Niepert, Mohamed Ahmed, and Konstantin Kutzkov · 2016
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Structural deep network embedding
Daixin Wang, Peng Cui, and Wenwu Zhu · 2016
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Scalable temporal latent space inference for link prediction in dynamic social networks
Linhong Zhu, Dong Guo, Junming Yin, Greg Ver Steeg, and Aram Galstyan · 2016
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Convolutional sequence to sequence learning
Jonas Gehring, Michael Auli, David Grangier, Denis Yarats, and Yann N. Dauphin · 2017
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Dyngem: Deep embedding method for dynamic graphs
Palash Goyal, Nitin Kamra, Xinran He, and Yan Liu · 2017
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An adversarial approach to improve long-tail performance in neural collaborative filtering
Adit Krishnan, Ashish Sharma, Aravind Sankar, and Hari Sundaram · 2018
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Learning dynamic embeddings from temporal interactions
Srijan Kumar, Xikun Zhang, and Jure Leskovec · 2018
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Streaming link prediction on dynamic attributed networks
Jundong Li, Kewei Cheng, Liang Wu, and Huan Liu · 2018
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Yao Ma, Ziyi Guo, Zhaochun Ren, Eric Zhao, Jiliang Tang, and Dawei Yin · 2018
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Continuous-time dynamic network embeddings
Giang Hoang Nguyen, John Boaz Lee, Ryan A Rossi, Nesreen K Ahmed, Eunyee Koh, and Sungchul Kim · 2018
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Inductive representation learning on large graphs
William L. Hamilton, Zhitao Ying, and Jure Leskovec · 2017
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Semi-supervised classification with graph convolutional networks
Thomas N Kipf and Max Welling · 2017
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Improving latent user models in online social media
Adit Krishnan, Ashish Sharma, and Hari Sundaram · 2017
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Attributed network embedding for learning in a dynamic environment
Jundong Li, Harsh Dani, Xia Hu, Jiliang Tang, Yi Chang, and Huan Liu · 2017
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A structured self-attentive sentence embedding
Zhouhan Lin, Minwei Feng, Cicero Nogueira dos Santos, Mo Yu, Bing Xiang, Bowen Zhou, and Yoshua Bengio · 2017
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Motif-based convolutional neural network on graphs
Aravind Sankar, Xinyang Zhang, and Kevin Chen-Chuan Chang · 2017
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Peter Shaw, Jakob Uszkoreit, and Ashish Vaswani · 2018
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Disan: Directional self-attention network for rnn/cnn-free language understanding
Tao Shen, Tianyi Zhou, Guodong Long, Jing Jiang, Shirui Pan, and Chengqi Zhang · 2018
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Deep semantic role labeling with self-attention
Zhixing Tan, Mingxuan Wang, Jun Xie, Yidong Chen, and Xiaodong Shi · 2018
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Representation learning over dynamic graphs
Rakshit Trivedi, Mehrdad Farajtbar, Prasenjeet Biswal, and Hongyuan Zha · 2018
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Graph attention networks
Petar Velickovic, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Lio, and Yoshua Bengio · 2018
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Graph convolutional neural networks for web-scale recommender systems
Rex Ying, Ruining He, Kaifeng Chen, Pong Eksombatchai, William L Hamilton, and Jure Leskovec · 2018
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Qanet: Combining local convolution with global self-attention for reading comprehension
Adams Wei Yu, David Dohan, Minh-Thang Luong, Rui Zhao, Kai Chen, Mohammad Norouzi, and Quoc V. Le · 2018
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Dynamic network embedding by modeling triadic closure process
Le-kui Zhou, Yang Yang, Xiang Ren, Fei Wu, and Yueting Zhuang · 2018
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Modeling polypharmacy side effects with graph convolutional networks
Marinka Zitnik, Monica Agrawal, and Jure Leskovec · 2018
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Embedding temporal network via neighborhood formation
Yuan Zuo, Guannan Liu, Hao Lin, Jia Guo, Xiaoqian Hu, and Junjie Wu · 2018
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