235 citations · 609 across the 5 of their papers we have counts for
5 papers
DeceFL: A Principled Decentralized Federated Learning Framework
Ye Yuan, Jun Liu, Dou Jin +12
Traditional machine learning relies on a centralized data pipeline, i.e., data are provided to a central server for model training. In many applications, however, data are inherent…
Machine Discovery of Partial Differential Equations from Spatiotemporal Data
Ye Yuan, Junlin Li, Liang Li +9
The study presents a general framework for discovering underlying Partial Differential Equations (PDEs) using measured spatiotemporal data. The method, called Sparse Spatiotemporal…
A General End-to-end Diagnosis Framework for Manufacturing Systems
Ye Yuan, Guijun Ma, Cheng Cheng +4
The manufacturing sector is envisioned to be heavily influenced by artificial intelligence-based technologies with the extraordinary increases in computational power and data volum…
A deep learning-based remaining useful life prediction approach for bearings
Cheng Cheng, Guijun Ma, Yong Zhang +4
In industrial applications, nearly half the failures of motors are caused by the degradation of rolling element bearings (REBs). Therefore, accurately estimating the remaining usef…
Data-driven Discovery of Cyber-Physical Systems
Ye Yuan, Xiuchuan Tang, Wei Pan +5
Cyber-physical systems (CPSs) embed software into the physical world. They appear in a wide range of applications such as smart grids, robotics, intelligent manufacture and medical…