Jian Tang (唐建）

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Meng QuQuebec AI Institute (Mila)Patvirtintas el. paštas umontreal.ca
Ming Zhang（张铭）Professor,Peking UniversityPatvirtintas el. paštas pku.edu.cn
Qiaozhu MeiProfessor, University of MichiganPatvirtintas el. paštas umich.edu
Chence ShiQuebec AI Institute (Mila)Patvirtintas el. paštas umontreal.ca
Zhaocheng ZhuMila - Quebec AI InstitutePatvirtintas el. paštas umontreal.ca
Minkai XuStanford UniversityPatvirtintas el. paštas cs.stanford.edu
Shengchao LiuUC BerkeleyPatvirtintas el. paštas berkeley.edu
Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFARPatvirtintas el. paštas umontreal.ca
Zhi-Hong DengSchool of Intelligence Science and Technology, Peking UniversityPatvirtintas el. paštas pku.edu.cn
Zhiyuan LiuAssociate Professor, Tsinghua UniversityPatvirtintas el. paštas tsinghua.edu.cn
Weiping Song (宋卫平)Peking UniversityPatvirtintas el. paštas pku.edu.cn
Andreea DeacIsomorphic LabsPatvirtintas el. paštas google.com
Feixiong ChengCleveland ClinicPatvirtintas el. paštas ccf.org
Laurent CharlinAssociate Professor, HEC Montréal & Mila, Canada CIFAR AI ChairPatvirtintas el. paštas hec.ca
Connor W. ColeyMassachusetts Institute of TechnologyPatvirtintas el. paštas mit.edu
XuanLong NguyenUniversity of MichiganPatvirtintas el. paštas umich.edu
Rafael Gómez-BombarelliAssociate Professor, MIT DMSEPatvirtintas el. paštas mit.edu
Xuanzhe LiuBoya Distinguished Professor, Peking University, ACM Distinguished ScientistPatvirtintas el. paštas pku.edu.cn
Bolanle OjokohDepartment of Information Systems, Federal University of Technology, Akure, NigeriaPatvirtintas el. paštas futa.edu.ng
Jian PengHelixonPatvirtintas el. paštas helixon.com

Stebėti

Jian Tang (唐建）

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

Patvirtintas el. paštas hec.ca - Pagrindinis puslapis

Geometric deep learning AI for molecule/protein design knowledge graphs deep generative models


Pavadinimas Rūšiuoti pagal šaltinius Rūšiuoti pagal metus Rūšiuoti pagal pavadinimą	Cituota Cituota	Metai
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	6581	2015
Rotate: Knowledge graph embedding by relational rotation in complex space Z Sun, ZH Deng, JY Nie, J Tang ICLR 2019, 2019	2879	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	1145	2020
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	990	2015
Scientific discovery in the age of artificial intelligence H Wang, T Fu, Y Du, W Gao, K Huang, Z Liu, P Chandak, S Liu, ... Nature 620 (7972), 47-60, 2023	932	2023
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	903	2019
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	769	2021
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	636	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	579	2022
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	546	2020
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	540	2016
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	514	2019
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	513	2020
Pre-training Molecular Graph Representation with 3D Geometry S Liu, H Wang, W Liu, J Lasenby, H Guo, J Tang ICLR 2022, 2022	390	2022
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	390	2014
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	368	2021
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	346	2021
GMNN: Graph Markov Neural Networks M Qu, Y Bengio, J Tang ICML 2019, 2019	341	2019
Adversarial network embedding Q Dai, Q Li, J Tang, D Wang Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018	267	2018
Self-supervised Graph-level Representation Learning with Local and Global Structure M Xu, H Wang, B Ni, H Guo, J Tang ICML’21, 2021	246	2021

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