Muhan Zhang

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Yixin ChenProfessor of Computer Science, Washington UniversityDirección de correo verificada de cse.wustl.edu
Zhicheng CuiGoogleDirección de correo verificada de google.com
Pan LiGeorgia Institute of Technology, Purdue UniversityDirección de correo verificada de gatech.edu
Yinglong XiaFacebookDirección de correo verificada de ieee.org
Marion NeumannWashington University in St. LouisDirección de correo verificada de wustl.edu
Xiaoxiao LiAssistant Professor, University of British Columbia; Vector Institute; CIFAR AI ChairDirección de correo verificada de ece.ubc.ca
Christopher Ryan KingWashington University in St LouisDirección de correo verificada de wustl.edu
Shali JiangFacebookDirección de correo verificada de wustl.edu
Michael AvidanProfessor of Anesthesiology, Washington UniversityDirección de correo verificada de wustl.edu
Yinjie TangProfessor of Chemical Engineering, Washington UniversityDirección de correo verificada de seas.wustl.edu
Wenbin CaiMicrosoftDirección de correo verificada de microsoft.com
Ya ZhangShanghai Jiao Tong UniversityDirección de correo verificada de sjtu.edu.cn
Hanqing ZengMeta; Ph.D. in computer engineeringDirección de correo verificada de meta.com
Viktor K. PrasannaUniversity of Southern CaliforniaDirección de correo verificada de usc.edu
Bradley FritzAssistant Professor, Washington University in St. LouisDirección de correo verificada de wustl.edu
Roman GarnettWashington University in St. LouisDirección de correo verificada de wustl.edu
Tolutola OyetundeTakedaDirección de correo verificada de takeda.com
Lian HeUniversity of Washington, Washington University in St. LouisDirección de correo verificada de uw.edu
Stephen Gang WuMerck, Express Scripts, MilliporeSigma, Washington UniversityDirección de correo verificada de go.wustl.edu

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Muhan Zhang

Peking University

Dirección de correo verificada de pku.edu.cn - Página principal

Machine Learning Graph Neural Network


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
Link prediction based on graph neural networks M Zhang, Y Chen Advances in Neural Information Processing Systems 31, 5165-5175, 2018	1985	2018
An End-to-End Deep Learning Architecture for Graph Classification M Zhang, Z Cui, M Neumann, Y Chen AAAI, 4438-4445, 2018	1685	2018
Braingnn: Interpretable brain graph neural network for fmri analysis X Li, Y Zhou, N Dvornek, M Zhang, S Gao, J Zhuang, D Scheinost, ... Medical Image Analysis 74, 102233, 2021	371	2021
Inductive matrix completion based on graph neural networks M Zhang, Y Chen International Conference on Learning Representations (ICLR 2020), 2020	282	2020
Weisfeiler-Lehman Neural Machine for Link Prediction M Zhang, Y Chen Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge …, 2017	254	2017
Labeling Trick: A Theory of Using Graph Neural Networks for Multi-Node Representation Learning M Zhang, P Li, Y Xia, K Wang, L Jin Advances in Neural Information Processing Systems 34, 2021	208*	2021
D-vae: A variational autoencoder for directed acyclic graphs M Zhang, S Jiang, Z Cui, R Garnett, Y Chen Advances in Neural Information Processing Systems, 1588-1600, 2019	170	2019
Decoupling the Depth and Scope of Graph Neural Networks H Zeng, M Zhang, Y Xia, A Srivastava, A Malevich, R Kannan, V Prasanna, ... Advances in Neural Information Processing Systems 34, 2021	168*	2021
How powerful are spectral graph neural networks X Wang, M Zhang International Conference on Machine Learning, 23341-23362, 2022	144	2022
Beyond Link Prediction: Predicting Hyperlinks in Adjacency Space M Zhang, Z Cui, S Jiang, Y Chen AAAI, 4430-4437, 2018	137*	2018
Nested Graph Neural Networks M Zhang, P Li Advances in Neural Information Processing Systems 34, 2021	131	2021
Deep-learning model for predicting 30-day postoperative mortality BA Fritz, Z Cui, M Zhang, Y He, Y Chen, A Kronzer, AB Abdallah, CR King, ... British Journal of Anaesthesia 123 (5), 688-695, 2019	96	2019
Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks H Wang, H Yin, M Zhang, P Li International Conference on Learning Representations, 2021	90	2021
Batch mode active learning for regression with expected model change W Cai, M Zhang, Y Zhang IEEE transactions on neural networks and learning systems 28 (7), 1668-1681, 2017	83	2017
How powerful are k-hop message passing graph neural networks J Feng, Y Chen, F Li, A Sarkar, M Zhang Advances in Neural Information Processing Systems 35, 4776-4790, 2022	66	2022
Pooling regularized graph neural network for fmri biomarker analysis X Li, Y Zhou, NC Dvornek, M Zhang, J Zhuang, P Ventola, JS Duncan Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020	64	2020
Boostgapfill: Improving the fidelity of metabolic network reconstructions through integrated constraint and pattern-based methods T Oyetunde, M Zhang, Y Chen, Y Tang, C Lo Bioinformatics 33 (4), 608-611, 2017	49	2017
3DLinker: An E (3) Equivariant Variational Autoencoder for Molecular Linker Design Y Huang, X Peng, J Ma, M Zhang arXiv preprint arXiv:2205.07309, 2022	38	2022
WUFlux: an open-source platform for ¹³C metabolic flux analysis of bacterial metabolism L He, SG Wu, M Zhang, Y Chen, YJ Tang BMC bioinformatics 17, 1-7, 2016	38	2016
Hierarchical Attention Propagation for Healthcare Representation Learning M Zhang, CR King, M Avidan, Y Chen Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020	35	2020

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