Suivre
Jian Tang (唐建）
Jian Tang (唐建）
Associate Professor, Mila-Quebec AI Institute, HEC Montréal, Canada CIFAR AI Chair
Adresse e-mail validée de hec.ca - Page d'accueil
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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
53862015
Rotate: Knowledge graph embedding by relational rotation in complex space
Z Sun, ZH Deng, JY Nie, J Tang
ICLR 2019, 2019
14842019
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
8452015
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
5562020
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
4522019
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
4362016
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
4222018
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
3732020
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
3442021
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
3362014
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
3332019
GMNN: Graph Markov Neural Networks
M Qu, Y Bengio, J Tang
ICML 2019, 2019
2692019
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
2472020
Adversarial network embedding
Q Dai, Q Li, J Tang, D Wang
Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018
2352018
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
1642017
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
1422021
Probabilistic Logic Neural Networks for Reasoning
M Qu, J Tang
NeurIPS'19, 2019
1362019
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
1312022
Graphmix: Regularized training of graph neural networks for semi-supervised learning
V Verma, M Qu, A Lamb, Y Bengio, J Kannala, J Tang
AAAI'21, 2021
112*2021
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
1042019
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