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 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
Chence ShiQuebec AI Institute (Mila)Verified email at umontreal.ca
Minkai XuStanford UniversityVerified email at stanford.edu
Zhaocheng ZhuMila - Quebec AI InstituteVerified email at umontreal.ca
Zhi-Hong DengSchool of Electronics Engineering and Computer Science, Peking UniversityVerified email at pku.edu.cn
Zhiyuan LiuAssociate Professor, Tsinghua UniversityVerified email at tsinghua.edu.cn
Weiping Song (宋卫平)Peking UniversityVerified email at pku.edu.cn
Andreea DeacMila, Université de MontréalVerified email at mila.quebec
Shengchao(Chao) LiuMILA-UdeMVerified email at umontreal.ca
XuanLong NguyenUniversity of MichiganVerified email at umich.edu
Feixiong ChengCleveland ClinicVerified email at ccf.org
Laurent CharlinAssociate 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
Xuanzhe LiuPeking UniversityVerified email at pku.edu.cn
Connor W. ColeyDepartment of Chemical Engineering, MITVerified email at mit.edu
Bolanle OjokohDepartment of Information Systems, Federal University of Technology, Akure, NigeriaVerified email at futa.edu.ng
Jian PengUniversity of Illinois at Urbana-ChampaignVerified email at illinois.edu

Jian Tang (唐建）

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

Verified email at hec.ca - Homepage

Geometric deep learning AI for molecule/protein design knowledge graphs 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	4699	2015
Rotate: Knowledge graph embedding by relational rotation in complex space Z Sun, ZH Deng, JY Nie, J Tang ICLR 2019, 2019	986	2019
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	756	2015
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	375	2016
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	350	2020
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	339	2018
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	318	2019
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	310	2014
Artificial intelligence in COVID-19 drug repurposing Y Zhou, F Wang, J Tang, R Nussinov, F Cheng The Lancet Digital Health 2 (12), e667-e676, 2020	280	2020
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	249	2019
GMNN: Graph Markov Neural Networks M Qu, Y Bengio, J Tang ICML 2019, 2019	223	2019
Adversarial network embedding Q Dai, Q Li, J Tang, D Wang Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018	211	2018
KEPLER: A unified model for knowledge embedding and pre-trained language representation X Wang, T Gao, Z Zhu, Z Zhang, Z Liu, J Li, J Tang Transactions of the Association for Computational Linguistics 9, 176-194, 2021	203	2021
GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation C Shi, M Xu, Z Zhu, W Zhang, M Zhang, J Tang ICLR 2020, 2020	164	2020
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	134	2017
Probabilistic Logic Neural Networks for Reasoning M Qu, J Tang NeurIPS'19, 2019	97	2019
GraphVite: A High-Performance CPU-GPU Hybrid System for Node Embedding Z Zhu, S Xu, M Qu, J Tang The World Wide Web Conference, 2494-2504, 2019	86	2019
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	74	2016
A Graph to Graphs Framework for Retrosynthesis Prediction C Shi, M Xu, H Guo, M Zhang, J Tang ICML'20, 2020	72	2020
Utilizing graph machine learning within drug discovery and development T Gaudelet, B Day, AR Jamasb, J Soman, C Regep, G Liu, JBR Hayter, ... Briefings in bioinformatics 22 (6), bbab159, 2021	71	2021

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