Mufei Li

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George KarypisDistinguished McKnight University Professor, University of Minnesota; SPS, AWSVerified email at umn.edu
Minjie WangAWS Shanghai AI LabVerified email at nyu.edu
Xiang SongSenior Applied Scientist at Amazon AWSVerified email at amazon.com
Zheng ZhangProfessor of Computer Science and Engineering, NYU Shanghai; Director, Amazon Shanghai AI LabVerified email at nyu.edu
Vassilis N. Ioannidis, PhDAmazonVerified email at amazon.com
Xia NingProfessor, Biomedical Informatics, Computer Science and Engineering, The Ohio StateVerified email at osu.edu
Saurav ManchandaAmazonVerified email at umn.edu
Xiangxiang ZengDeparment of Computer Science, Hunan UniversityVerified email at hnu.edu.cn
Jiajing HuPhD student, King's College LondonVerified email at kcl.ac.uk
Pan LiGeorgia Institute of Technology, Purdue UniversityVerified email at gatech.edu
Fabio BroccatelliDirector at Altos LabsVerified email at altoslabs.com
Eli ChienGeorgia Institute of TechnologyVerified email at gatech.edu
Xingjian ShiBoson AIVerified email at connect.ust.hk
Tushar KrishnaAssociate Professor, Georgia TechVerified email at ece.gatech.edu
Srinivas Sridharan, PhdDistinguished Engineer, NVIDIAVerified email at nvidia.com
Siqi MiaoGeorgia Institute of TechnologyVerified email at gatech.edu
Zhaodong WangResearch Scientist, FacebookVerified email at fb.com

Mufei Li

Georgia Institute of Technology

Verified email at gatech.edu - Homepage

Machine Learning Graph Neural Networks Generative Models


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Deep graph library: A graph-centric, highly-performant package for graph neural networks M Wang, D Zheng, Z Ye, Q Gan, M Li, X Song, J Zhou, C Ma, L Yu, Y Gai, ... arXiv preprint arXiv:1909.01315, 2019	1318	2019
Deep graph library: Towards efficient and scalable deep learning on graphs M Wang, L Yu, D Zheng, Q Gan, Y Gai, Z Ye, M Li, J Zhou, Q Huang, C Ma, ... ICLR workshop on representation learning on graphs and manifolds, 2019	822	2019
Dgl-lifesci: An open-source toolkit for deep learning on graphs in life science M Li, J Zhou, J Hu, W Fan, Y Zhang, Y Gu, G Karypis ACS Omega, 2021	165	2021
Drkg-drug repurposing knowledge graph for covid-19 VN Ioannidis, X Song, S Manchanda, M Li, X Pan, D Zheng, X Ning, ... https://github.com/gnn4dr/DRKG, 2020	123*	2020
A knowledge graph of clinical trials (CTKG) Z Chen, B Peng, VN Ioannidis, M Li, G Karypis, X Ning Scientific reports 12 (1), 4724, 2022	19*	2022
Benchmarking Accuracy and Generalizability of Four Graph Neural Networks Using Large In Vitro ADME Datasets from Different Chemical Spaces F Broccatelli, R Trager, M Reutlinger, G Karypis, M Li Molecular Informatics (top 10 most-cited papers, 2022 - 2023), 2022	17	2022
De novo generation of dual-target ligands using adversarial training and reinforcement learning F Lu, M Li, X Min, C Li, X Zeng Briefings in Bioinformatics 22 (6), bbab333, 2021	15	2021
A statistical characterization of attentions in graph neural networks M Li, H Zhang, X Shi, M Wang, Z Zhang International Conference on Learning Representations (ICLR) 2019 Workshop on …, 2019	7	2019
GraphMaker: Can Diffusion Models Generate Large Attributed Graphs? M Li, E Kreačić, VK Potluru, P Li Transactions on Machine Learning Research (TMLR), 2023	4	2023
Graph Neural Networks in Life Sciences: Opportunities and Solutions Z Wang, VN Ioannidis, H Rangwala, T Arai, R Brand, M Li, Y Nakayama Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022	4	2022
Opportunities and challenges of graph neural networks in electrical engineering E Chien, M Li, A Aportela, K Ding, S Jia, S Maji, Z Zhao, J Duarte, V Fung, ... Nature Reviews Electrical Engineering 1 (8), 529-546, 2024	2	2024
LayerDAG: A Layerwise Autoregressive Diffusion Model for Directed Acyclic Graph Generation M Li, V Shitole, E Chien, C Man, Z Wang, S Sridharan, Y Zhang, T Krishna, ... arXiv preprint arXiv:2411.02322, 2024		2024
Simple is Effective: The Roles of Graphs and Large Language Models in Knowledge-Graph-Based Retrieval-Augmented Generation M Li, S Miao, P Li arXiv preprint arXiv:2410.20724 (*Equal contribution), 2024		2024
KGExplainer: Towards Exploring Connected Subgraph Explanations for Knowledge Graph Completion T Ma, W Tao, M Li, J Zhang, X Pan, J Lin, B Song, X Zeng arXiv preprint arXiv:2404.03893, 2024		2024

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