4 citations · 7 across the 3 of their papers we have counts for
3 papers
cs.LG2019★ 2 cited
Reinforcement Learning with Policy Mixture Model for Temporal Point Processes Clustering
Weichang Wu, Junchi Yan, Xiaokang Yang +1
Temporal point process is an expressive tool for modeling event sequences over time. In this paper, we take a reinforcement learning view whereby the observed sequences are assumed…
cs.LG2018★ 4 cited
Decoupled Learning for Factorial Marked Temporal Point Processes
Weichang Wu, Junchi Yan, Xiaokang Yang +1
This paper introduces the factorial marked temporal point process model and presents efficient learning methods. In conventional (multi-dimensional) marked temporal point process m…
cs.LG2016★ 1 cited
Patient Flow Prediction via Discriminative Learning of Mutually-Correcting Processes
Hongteng Xu, Weichang Wu, Shamim Nemati +1
Over the past decade the rate of care unit (CU) use in the United States has been increasing. With an aging population and ever-growing demand for medical care, effective managemen…