| Mxnet: A flexible and efficient machine learning library for heterogeneous distributed systems T Chen, M Li, Y Li, M Lin, N Wang, M Wang, T Xiao, B Xu, C Zhang, ... arXiv preprint arXiv:1512.01274, 2015 | 2864 | 2015 |
| 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 | 2112* | 2019 |
| DistDGL: Distributed graph neural network training for billion-scale graphs D Zheng, C Ma, M Wang, J Zhou, Q Su, X Song, Q Gan, Z Zhang, ... 2020 IEEE/ACM 10th Workshop on Irregular Applications: Architectures and …, 2020 | 256* | 2020 |
| Supporting very large models using automatic dataflow graph partitioning M Wang, C Huang, J Li Proceedings of the Fourteenth EuroSys Conference 2019, 1-17, 2019 | 186 | 2019 |
| Featgraph: A flexible and efficient backend for graph neural network systems Y Hu, Z Ye, M Wang, J Yu, D Zheng, M Li, Z Zhang, Z Zhang, Y Wang SC20: International Conference for High Performance Computing, Networking …, 2020 | 95 | 2020 |
| Mxnet: A flexible and efficient machine learning library for heterogeneous distributed systems. arXiv 2015 T Chen, M Li, Y Li, M Lin, N Wang, M Wang, T Xiao, B Xu, C Zhang, ... arXiv preprint arXiv:1512.01274, 0 | 88 | |
| Distributed hybrid cpu and gpu training for graph neural networks on billion-scale heterogeneous graphs D Zheng, X Song, C Yang, D LaSalle, G Karypis Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 60 | 2022 |
| Deep graph library: A graph-centric, highly-performant package for graph neural networks. arXiv M Wang, D Zheng, Z Ye, Q Gan, M Li, X Song, J Zhou, C Ma, L Yu, Y Gai, ... Learning, 2019 | 39 | 2019 |
| Minerva: A scalable and highly efficient training platform for deep learning M Wang, T Xiao, J Li, J Zhang, C Hong, Z Zhang NIPS Workshop, Distributed Machine Learning and Matrix Computations, 51, 2014 | 33 | 2014 |
| Unifying data, model and hybrid parallelism in deep learning via tensor tiling M Wang, C Huang, J Li arXiv preprint arXiv:1805.04170, 2018 | 29 | 2018 |
| Impression store: Compressive sensing-based storage for big data analytics J Zhang, Y Yan, LJ Chen, M Wang, T Moscibroda, Z Zhang 6th USENIX Workshop on Hot Topics in Cloud Computing (HotCloud 14), 2014 | 25 | 2014 |
| Scalable graph neural networks with deep graph library D Zheng, M Wang, Q Gan, X Song, Z Zhang, G Karypis Proceedings of the 14th ACM International Conference on Web Search and Data …, 2021 | 24 | 2021 |
| Graphiler: Optimizing graph neural networks with message passing data flow graph Z Xie, M Wang, Z Ye, Z Zhang, R Fan | 24 | 2021 |
| Learning graph neural networks with deep graph library D Zheng, M Wang, Q Gan, Z Zhang, G Karypis Companion Proceedings of the Web Conference 2020, 305-306, 2020 | 21 | 2020 |
| Viscous dissipation influencing viscosity of polymer melt in micro channels B Xu, M Wang, T Yu, D Zhao Journal of Mechanical science and technology 24, 1417-1423, 2010 | 18 | 2010 |
| Study on viscosity of polymer melt flowing through microchannels considering the wall‐slip effect D Zhao, Y Jin, M Wang Polymer Engineering & Science 52 (8), 1806-1814, 2012 | 16 | 2012 |
| Theoretical and experimental approach of the viscosity of polymer melt under micro-scale effect 徐斌， 王敏杰， 于同敏， 赵丹阳 Journal of Mechanical Engineering 46 (19), 125-132, 2010 | 15 | 2010 |
| Microcosmic mechanism of material softening and fracture in primary shear zone during high speed machining of hardened steel CZ Duan, MJ Wang, YJ Cai, T Dou Materials Science and Technology 27 (3), 625-630, 2011 | 14 | 2011 |
| Form error compensation in ball-end milling of sculptured surface with z-level contouring tool path ZC Wei, MJ Wang, WC Tang, JN Zhu, GC Xia The International Journal of Advanced Manufacturing Technology 67, 2853-2861, 2013 | 13 | 2013 |
| Numerical simulation and experimental study of polymer micro extrusion flow D Zhao, Y Jin, M Wang, K Li, M Song 2009 International Conference on Mechatronics and Automation, 3155-3160, 2009 | 13 | 2009 |
Zheng ZhangProfessor of Computer Science and Engineering, NYU Shanghai; Director, Amazon Shanghai AI LabVerified email at nyu.edu
