no code implementations • 19 Dec 2023 • Youshao Xiao, Weichang Wu, Zhenglei Zhou, Fagui Mao, Shangchun Zhao, Lin Ju, Lei Liang, Xiaolu Zhang, Jun Zhou
Furthermore, our framework provides a simple user interface and allows for the agile allocation of models across devices in a fine-grained manner for various training scenarios, involving models of varying sizes and devices of different scales.
no code implementations • 5 Aug 2019 • Weichang Wu, Huanxi Liu, Xiaohu Zhang, Yu Liu, Hongyuan Zha
Temporal point process is widely used for sequential data modeling.
no code implementations • 29 May 2019 • Weichang Wu, Junchi Yan, Xiaokang Yang, Hongyuan Zha
Temporal point process is an expressive tool for modeling event sequences over time.
no code implementations • 21 Jan 2018 • Weichang Wu, Junchi Yan, Xiaokang Yang, Hongyuan Zha
In conventional (multi-dimensional) marked temporal point process models, event is often encoded by a single discrete variable i. e. a marker.
no code implementations • 14 Feb 2016 • Hongteng Xu, Weichang Wu, Shamim Nemati, Hongyuan Zha
By treating a sequence of transition events as a point process, we develop a novel framework for modeling patient flow through various CUs and jointly predicting patients' destination CUs and duration days.