Jian Tang (唐建）

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Meng QuQuebec AI Institute (Mila)Verified email at umontreal.ca
Ming Zhang, 张铭Professor,Peking UniversityVerified email at net.pku.edu.cn
Qiaozhu MeiProfessor, University of MichiganVerified email at umich.edu
Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFARVerified email at umontreal.ca
Zhi-Hong DengSchool of Electronics Engineering and Computer Science, Peking UniversityVerified email at cis.pku.edu.cn
Weiping Song (宋卫平)Peking UniversityVerified email at pku.edu.cn
Chence ShiQuebec AI Institute (Mila)Verified email at umontreal.ca
Minkai XuMila - Quebec AI InstituteVerified email at umontreal.ca
Zhaocheng ZhuQuebec AI Institute (Mila)Verified email at umontreal.ca
XuanLong NguyenUniversity of MichiganVerified email at umich.edu
Zhaoshi MengVicarious AIVerified email at vicarious.com
Zhiyuan LiuAssociate Professor, Tsinghua UniversityVerified email at tsinghua.edu.cn
Xuanzhe LiuPeking UniversityVerified email at pku.edu.cn
Bolanle OjokohProfessor of Computer Science, Federal University of Technology, Akure, NigeriaVerified email at futa.edu.ng
Andreea DeacMila, Université de MontréalVerified email at mila.quebec
Laurent CharlinAssistant Professor, HEC Montréal & Mila, Canada CIFAR AI ChairVerified email at hec.ca
P. Lió, Pietro Lio, P. Lio, Pietro Liò, Pie...University of CambridgeVerified email at cam.ac.uk
Yong LuoNanyang Technological UniversityVerified email at ntu.edu.sg
Shengchao(Chao) LiuUniversity of MontrealVerified email at umontreal.ca
zheng chenPrinciple Researcher of Microsoft Research AsiaVerified email at microsoft.com

Jian Tang (唐建）

Assistant Professor, Mila-Quebec AI Institute, HEC Montréal, Canada CIFAR AI Chair

Verified email at hec.ca - Homepage

Deep learning graph representation learning knowledge graphs drug discovery deep generative models


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Line: Large-scale information network embedding J Tang, M Qu, M Wang, M Zhang, J Yan, Q Mei Proceedings of the 24th international conference on world wide web, 1067-1077, 2015	3244	2015
Pte: Predictive text embedding through large-scale heterogeneous text networks J Tang, M Qu, Q Mei Proceedings of the 21th ACM SIGKDD international conference on knowledge …, 2015	545	2015
Rotate: Knowledge graph embedding by relational rotation in complex space Z Sun, ZH Deng, JY Nie, J Tang ICLR 2019, 2019	337	2019
Visualizing large-scale and high-dimensional data J Tang, J Liu, M Zhang, Q Mei Proceedings of the 25th international conference on world wide web, 287-297, 2016	273	2016
Understanding the limiting factors of topic modeling via posterior contraction analysis J Tang, Z Meng, X Nguyen, Q Mei, M Zhang International Conference on Machine Learning, 190-198, 2014	228	2014
Deepinf: Social influence prediction with deep learning J Qiu, J Tang, H Ma, Y Dong, K Wang, J Tang Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018	150	2018
Correlated states in twisted double bilayer graphene C Shen, Y Chu, QS Wu, N Li, S Wang, Y Zhao, J Tang, J Liu, J Tian, ... Nature Physics 16 (5), 520-525, 2020	149	2020
Adversarial network embedding Q Dai, Q Li, J Tang, D Wang Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018	138	2018
Graphene‐Contacted Ultrashort Channel Monolayer MoS₂ Transistors L Xie, M Liao, S Wang, H Yu, L Du, J Tang, J Zhao, J Zhang, P Chen, X Lu, ... Advanced Materials 29 (37), 1702522, 2017	130	2017
Session-based social recommendation via dynamic graph attention networks W Song, Z Xiao, Y Wang, L Charlin, M Zhang, J Tang Proceedings of the Twelfth ACM International Conference on Web Search and …, 2019	105	2019
Thermally induced graphene rotation on hexagonal boron nitride D Wang, G Chen, C Li, M Cheng, W Yang, S Wu, G Xie, J Zhang, J Zhao, ... Physical review letters 116 (12), 126101, 2016	105	2016
GMNN: Graph Markov Neural Networks M Qu, Y Bengio, J Tang ICML 2019, 2019	99	2019
AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks W Song, C Shi, Z Xiao, Z Duan, Y Xu, M Zhang, J Tang CIKM 2019, 2019	95	2019
An attention-based collaboration framework for multi-view network representation learning M Qu, J Tang, J Shang, X Ren, M Zhang, J Han Proceedings of the 2017 ACM on Conference on Information and Knowledge …, 2017	92	2017
Current-driven magnetization switching in a van der Waals ferromagnet Fe3GeTe2 X Wang, J Tang, X Xia, C He, J Zhang, Y Liu, C Wan, C Fang, C Guo, ... Science advances 5 (8), eaaw8904, 2019	78	2019
InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization FY Sun, J Hoffmann, V Verma, J Tang ICLR 2020 (Spotlight), 2020	76	2020
Artificial intelligence in COVID-19 drug repurposing Y Zhou, F Wang, J Tang, R Nussinov, F Cheng The Lancet Digital Health, 2020	70	2020
Context-aware natural language generation with recurrent neural networks J Tang, Y Yang, S Carton, M Zhang, Q Mei arXiv preprint arXiv:1611.09900, 2016	60	2016
Biosurfactants enhanced heavy metals removal from sludge in the electrokinetic treatment J Tang, J He, X Xin, H Hu, T Liu Chemical Engineering Journal 334, 2579-2592, 2018	59	2018
One theme in all views: modeling consensus topics in multiple contexts J Tang, M Zhang, Q Mei Proceedings of the 19th ACM SIGKDD international conference on Knowledge …, 2013	59	2013

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