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DeepGraphLearning / repository
A comprehensive collection of recent papers on graph deep learning
Literature of Deep Learning for Graphs
This is a paper list about deep learning for graphs.
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DeepWalk: Online Learning of Social Representations <https://arxiv.org/pdf/1403.6652>_
| :authors:Bryan Perozzi, Rami Al-Rfou, Steven Skiena
| :venue:KDD 2014
| :keywords:Node classification, Random walk, Skip-gram
LINE: Large-scale Information Network Embedding <https://arxiv.org/pdf/1503.03578>_
| :authors:Jian Tang, Meng Qu, Mingzhe Wang, Ming Zhang, Jun Yan, Qiaozhu Mei
| :venue:WWW 2015
| :keywords:First-order, Second-order, Node classification
GraRep: Learning Graph Representations with Global Structural Information <https://dl.acm.org/citation.cfm?id=2806512>_
| :authors:Shaosheng Cao, Wei Lu, Qiongkai Xu
| :venue:CIKM 2015
| :keywords:High-order, SVD
node2vec: Scalable Feature Learning for Networks <https://arxiv.org/pdf/1607.00653>_
| :authors:Aditya Grover, Jure Leskovec
| :venue:KDD 2016
| :keywords:Breadth-first Search, Depth-first Search, Node Classification, Link Prediction
Variational Graph Auto-Encoders <https://arxiv.org/abs/1611.07308>_
| :authors:Thomas N. Kipf, Max Welling
| :venue:arXiv 2016
Scalable Graph Embedding for Asymmetric Proximity <https://aaai.org/ocs/index.php/AAAI/AAAI17/paper/view/14696>_
| :authors:Chang Zhou, Yuqiong Liu, Xiaofei Liu, Zhongyi Liu, Jun Gao
| :venue:AAAI 2017
Fast Network Embedding Enhancement via High Order Proximity Approximation <https://www.ijcai.org/proceedings/2017/544>_
| :authors:Cheng Yang, Maosong Sun, Zhiyuan Liu, Cunchao Tu
| :venue:IJCAI 2017
struc2vec: Learning Node Representations from Structural Identity <https://arxiv.org/pdf/1704.03165>_
| :authors:Leonardo F. R. Ribeiro, Pedro H. P. Savarese, Daniel R. Figueiredo
| :venue:KDD 2017
| :keywords:Structural Identity
Poincaré Embeddings for Learning Hierarchical Representations <https://arxiv.org/pdf/1705.08039>_
| :authors:Maximilian Nickel, Douwe Kiela
| :venue:NIPS 2017
VERSE: Versatile Graph Embeddings from Similarity Measures <https://arxiv.org/pdf/1803.04742>_
| :authors:Anton Tsitsulin, Davide Mottin, Panagiotis Karras, Emmanuel Müller
| :venue:WWW 2018
Network Embedding as Matrix Factorization: Unifying DeepWalk, LINE, PTE, and node2vec <https://arxiv.org/pdf/1710.02971>_
| :authors:Jiezhong Qiu, Yuxiao Dong, Hao Ma, Jian Li, Kuansan Wang, Jie Tang
| :venue:WSDM 2018
Learning Structural Node Embeddings via Diffusion Wavelets <https://arxiv.org/pdf/1710.10321>_
| :authors:Claire Donnat, Marinka Zitnik, David Hallac, Jure Leskovec
| :venue:KDD 2018
Adversarial Network Embedding <https://arxiv.org/pdf/1711.07838>_
| :authors:Quanyu Dai, Qiang Li, Jian Tang, Dan Wang
| :venue:AAAI 2018
GraphGAN: Graph Representation Learning with Generative Adversarial Nets <https://arxiv.org/pdf/1711.08267>_
| :authors:Hongwei Wang, Jia Wang, Jialin Wang, Miao Zhao, Weinan Zhang, Fuzheng Zhang, Xing Xie, Minyi Guo
| :venue:AAAI 2018
A General View for Network Embedding as Matrix Factorization <https://dl.acm.org/citation.cfm?id=3291029>_
| :authors:Xin Liu, Tsuyoshi Murata, Kyoung-Sook Kim, Chatchawan Kotarasu, Chenyi Zhuang
| :venue:WSDM 2019
Deep Graph Infomax <https://arxiv.org/pdf/1809.10341>_
| :authors:Petar Veličković, William Fedus, William L. Hamilton, Pietro Liò, Yoshua Bengio, R Devon Hjelm
| :venue:ICLR 2019
NetSMF: Large-Scale Network Embedding as Sparse Matrix Factorization <http://keg.cs.tsinghua.edu.cn/jietang/publications/www19-Qiu-et-al-NetSMF-Large-Scale-Network-Embedding.pdf>_
| :authors:Jiezhong Qiu, Yuxiao Dong, Hao Ma, Jian Li, Chi Wang, Kuansan Wang, Jie Tang
| :venue:WWW 2019
Adversarial Training Methods for Network Embedding <https://dl.acm.org/citation.cfm?id=3313445>_
| :authors:Quanyu Dai, Xiao Shen, Liang Zhang, Qiang Li, Dan Wang
| :venue:WWW 2019
vGraph: A Generative Model for Joint Community Detection and Node Representation Learning <https://arxiv.org/pdf/1906.07159.pdf>_
| :authors:Fan-Yun Sun, Meng Qu, Jordan Hoffmann, Chin-Wei Huang, Jian Tang
| :venue:NeurIPS 2019
ProGAN: Network Embedding via Proximity Generative Adversarial Network <https://dl.acm.org/citation.cfm?id=3330866>_
| :authors:Hongchang Gao, Jian Pei, Heng Huang
| :venue:KDD 2019
GraphZoom: A Multi-level Spectral Approach for Accurate and Scalable Graph Embedding <https://openreview.net/pdf?id=r1lGO0EKDH>_
| :authors:Chenhui Deng, Zhiqiang Zhao, Yongyu Wang, Zhiru Zhang, Zhuo Feng
| :venue:ICLR 2020
Learning Latent Representations of Nodes for Classifying in Heterogeneous Social Networks <https://dl.acm.org/citation.cfm?id=2556225>_
| :authors:Yann Jacob, Ludovic Denoyer, Patrick Gallinari
| :venue:WSDM 2014
PTE: Predictive Text Embedding through Large-scale Heterogeneous Text Networks <https://arxiv.org/pdf/1508.00200>_
| :authors:Jian Tang, Meng Qu, Qiaozhu Mei
| :venue:KDD 2015
| :keywords:Text Embedding, Heterogeneous Text Graphs
Heterogeneous Network Embedding via Deep Architectures <https://dl.acm.org/citation.cfm?id=2783296>_
| :authors:Shiyu Chang, Wei Han, Jiliang Tang, Guo-Jun Qi, Charu C. Aggarwal, Thomas S. Huang
| :venue:KDD 2015
Network Representation Learning with Rich Text Information <https://www.aaai.org/ocs/index.php/IJCAI/IJCAI15/paper/view/11098>_
| :authors:Cheng Yang, Zhiyuan Liu, Deli Zhao, Maosong Sun, Edward Chang
| :venue:AAAI 2015
Max-Margin DeepWalk: Discriminative Learning of Network Representation <https://www.ijcai.org/Proceedings/16/Papers/547.pdf>_
| :authors:Cunchao Tu, Weicheng Zhang, Zhiyuan Liu, Maosong Sun
| :venue:IJCAI 2016
metapath2vec: Scalable Representation Learning for Heterogeneous Networks <https://dl.acm.org/citation.cfm?id=3098036>_
| :authors:Yuxiao Dong, Nitesh V. Chawla, Ananthram Swami
| :venue:KDD 2017
Meta-Path Guided Embedding for Similarity Search in Large-Scale Heterogeneous Information Networks <https://arxiv.org/pdf/1610.09769>_
| :authors:Jingbo Shang, Meng Qu, Jialu Liu, Lance M. Kaplan, Jiawei Han, Jian Peng
| :venue:arXiv 2016
HIN2Vec: Explore Meta-paths in Heterogeneous Information Networks for Representation Learning <https://dl.acm.org/citation.cfm?id=3132953>_
| :authors:Tao-yang Fu, Wang-Chien Lee, Zhen Lei
| :venue:CIKM 2017
An Attention-based Collaboration Framework for Multi-View Network Representation Learning <https://arxiv.org/pdf/1709.06636>_
| :authors:Meng Qu, Jian Tang, Jingbo Shang, Xiang Ren, Ming Zhang, Jiawei Han
| :venue:CIKM 2017
Multi-view Clustering with Graph Embedding for Connectome Analysis <https://dl.acm.org/citation.cfm?id=3132909>_
| :authors:Guixiang Ma, Lifang He, Chun-Ta Lu, Weixiang Shao, Philip S. Yu, Alex D. Leow, Ann B. Ragin
| :venue:CIKM 2017
Attributed Signed Network Embedding <https://dl.acm.org/citation.cfm?id=3132847.3132905>_
| :authors:Suhang Wang, Charu Aggarwal, Jiliang Tang, Huan Liu
| :venue:CIKM 2017
CANE: Context-Aware Network Embedding for Relation Modeling <https://aclweb.org/anthology/papers/P/P17/P17-1158/>_
| :authors:Cunchao Tu, Han Liu, Zhiyuan Liu, Maosong Sun
| :venue:ACL 2017
PME: Projected Metric Embedding on Heterogeneous Networks for Link Prediction <https://dl.acm.org/citation.cfm?id=3219986>_
| :authors:Hongxu Chen, Hongzhi Yin, Weiqing Wang, Hao Wang, Quoc Viet Hung Nguyen, Xue Li
| :venue:KDD 2018
BiNE: Bipartite Network Embedding <https://dl.acm.org/citation.cfm?id=3209978.3209987>_
| :authors:Ming Gao, Leihui Chen, Xiangnan He, Aoying Zhou
| :venue:SIGIR 2018
StarSpace: Embed All The Things <https://arxiv.org/pdf/1709.03856>_
| :authors:Ledell Wu, Adam Fisch, Sumit Chopra, Keith Adams, Antoine Bordes, Jason Weston
| :venue:AAAI 2018
Exploring Expert Cognition for Attributed Network Embedding <https://dl.acm.org/citation.cfm?id=3159655>_
| :authors:Xiao Huang, Qingquan Song, Jundong Li, Xia Hu
| :venue:WSDM 2018
SHINE: Signed Heterogeneous Information Network Embedding for Sentiment Link Prediction <https://arxiv.org/pdf/1712.00732>_
| :authors:Hongwei Wang, Fuzheng Zhang, Min Hou, Xing Xie, Minyi Guo, Qi Liu
| :venue:WSDM 2018
Multidimensional Network Embedding with Hierarchical Structures <https://dl.acm.org/citation.cfm?id=3159680>_
| :authors:Yao Ma, Zhaochun Ren, Ziheng Jiang, Jiliang Tang, Dawei Yin
| :venue:WSDM 2018
Curriculum Learning for Heterogeneous Star Network Embedding via Deep Reinforcement Learning <https://dl.acm.org/citation.cfm?id=3159711>_
| :authors:Meng Qu, Jian Tang, Jiawei Han
| :venue:WSDM 2018
Generative Adversarial Network based Heterogeneous Bibliographic Network Representation for Personalized Citation Recommendation <https://www.semanticscholar.org/paper/Generative-Adversarial-Network-Based-Heterogeneous-Cai-Han/1596d6487012696ba400fb69904a2c372a08a2be>_
| :authors:Xiaoyan Cai, Junwei Han, Libin Yang
| :venue:AAAI 2018
ANRL: Attributed Network Representation Learning via Deep Neural Networks <https://www.ijcai.org/proceedings/2018/438>_
| :authors:Zhen Zhang, Hongxia Yang, Jiajun Bu, Sheng Zhou, Pinggang Yu, Jianwei Zhang, Martin Ester, Can Wang
| :venue:IJCAI 2018
Efficient Attributed Network Embedding via Recursive Randomized Hashing <https://www.ijcai.org/proceedings/2018/397>_
| :authors:Wei Wu, Bin Li, Ling Chen, Chengqi Zhang
| :venue:IJCAI 2018
Deep Attributed Network Embedding <https://www.ijcai.org/proceedings/2018/467>_
| :authors:Hongchang Gao, Heng Huang
| :venue:IJCAI 2018
Co-Regularized Deep Multi-Network Embedding <https://dl.acm.org/citation.cfm?id=3186113>_
| :authors:Jingchao Ni, Shiyu Chang, Xiao Liu, Wei Cheng, Haifeng Chen, Dongkuan Xu, Xiang Zhang
| :venue:WWW 2018
Easing Embedding Learning by Comprehensive Transcription of Heterogeneous Information Networks <https://arxiv.org/pdf/1807.03490>_
| :authors:Yu Shi, Qi Zhu, Fang Guo, Chao Zhang, Jiawei Han
| :venue:KDD 2018
Meta-Graph Based HIN Spectral Embedding: Methods, Analyses, and Insights <https://www.semanticscholar.org/paper/Meta-Graph-Based-HIN-Spectral-Embedding%3A-Methods%2C-Yang-Feng/4d5f4d6785d550383e3f3afb04c3015bf0d28405>_
| :authors:Carl Yang, Yichen Feng, Pan Li, Yu Shi, Jiawei Han
| :venue:ICDM 2018
SIDE: Representation Learning in Signed Directed Networks <https://dl.acm.org/citation.cfm?id=3186117>_
| :authors:Junghwan Kim, Haekyu Park, Ji-Eun Lee, U Kang
| :venue:WWW 2018
Learning Network-to-Network Model for Content-rich Network Embedding <https://dl.acm.org/citation.cfm?id=3330924>_
| :authors: Zhicheng He, Jie Liu, Na Li, Yalou Huang
| :venue:KDD 2019
Know-evolve: Deep temporal reasoning for dynamic knowledge graphs <https://arxiv.org/pdf/1705.05742.pdf>_
| :authors:Rakshit Trivedi, Hanjun Dai, Yichen Wang, Le Song
| :venue:ICML 2017
`Dyngem: Deep embedding method for dynamic graphs <https://arxiv.org/pdf/