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
Chence ShiQuebec AI Institute (Mila)Verified email at umontreal.ca
Minkai XuStanford UniversityVerified email at stanford.edu
Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFARVerified email at umontreal.ca
Zhaocheng ZhuMila - Quebec AI InstituteVerified email at umontreal.ca
Shengchao LiuUC Berkeley & CaltechVerified email at berkeley.edu
Zhi-Hong DengSchool of Intelligence Science and Technology, Peking UniversityVerified email at pku.edu.cn
Weiping Song (宋卫平)Peking UniversityVerified email at pku.edu.cn
Zhiyuan LiuAssociate Professor, Tsinghua UniversityVerified email at tsinghua.edu.cn
Andreea DeacMila, Université de MontréalVerified email at mila.quebec
Feixiong ChengCleveland ClinicVerified email at ccf.org
Laurent CharlinAssociate Professor, HEC Montréal & Mila, Canada CIFAR AI ChairVerified email at hec.ca
XuanLong NguyenUniversity of MichiganVerified email at umich.edu
Connor W. ColeyDepartment of Chemical Engineering, MITVerified email at mit.edu
Rafael Gómez-BombarelliAssociate Professor, MIT DMSEVerified email at mit.edu
Xuanzhe LiuPeking University | ACM Distinguished ScientistVerified email at pku.edu.cn
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	5841	2015
Rotate: Knowledge graph embedding by relational rotation in complex space Z Sun, ZH Deng, JY Nie, J Tang ICLR 2019, 2019	1873	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	883	2015
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	738	2020
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	612	2019
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	484	2018
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	470	2016
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	465	2021
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	416	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	389	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	347	2014
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	323	2020
GMNN: Graph Markov Neural Networks M Qu, Y Bengio, J Tang ICML 2019, 2019	298	2019
Adversarial network embedding Q Dai, Q Li, J Tang, D Wang Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018	243	2018
GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation M Xu, L Yu, Y Song, C Shi, S Ermon, J Tang ICLR 2022 Oral, 2022	242	2022
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	188	2021
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	178	2017
Probabilistic Logic Neural Networks for Reasoning M Qu, J Tang NeurIPS'19, 2019	162	2019
Pre-training Molecular Graph Representation with 3D Geometry S Liu, H Wang, W Liu, J Lasenby, H Guo, J Tang ICLR 2022, 2022	159	2022
Neural bellman-ford networks: A general graph neural network framework for link prediction Z Zhu, Z Zhang, LP Xhonneux, J Tang Advances in Neural Information Processing Systems 34, 29476-29490, 2021	148	2021

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