368 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Beijing Institute of TechnologyCN30 papers
- Beijing Electronic Science and Technology InstituteCN15 papers
- Institute of PhysicsPL4 papers
- Tsinghua UniversityCN4 papers
- Beijing Academy of Quantum Information SciencesCN2 papers
- Beijing Institute of Big Data ResearchCN2 papers
- Beijing Jiaotong UniversityCN2 papers
- Beijing University of Posts and TelecommunicationsCN2 papers
- Bielefeld UniversityDE2 papers
- China Datang Corporation (China)CN2 papers
- Chinese Academy of EngineeringCN2 papers
- Chinese Academy of SciencesCN2 papers
5 papers · 1 filter
Stochastic Heat Equations with Values in a Manifold via Dirichlet Forms
Michael Röckner, Bo Wu, Rongchan Zhu +1
In this paper, we prove the existence of martingale solutions to the stochastic heat equation taking values in a Riemannian manifold, which admits Wiener (Brownian bridge) measure…
Conceptualization Topic Modeling
Yi-Kun Tang, Xian-Ling Mao, Heyan Huang +1
Recently, topic modeling has been widely used to discover the abstract topics in text corpora. Most of the existing topic models are based on the assumption of three-layer hierarch…
Supervised Deep Hashing for Hierarchical Labeled Data
Dan Wang, Heyan Huang, Chi Lu +4
Recently, hashing methods have been widely used in large-scale image retrieval. However, most existing hashing methods did not consider the hierarchical relation of labels, which m…
Development and Evaluation of Two Learning-Based Personalized Driver Models for Car-Following Behaviors
Wenshuo Wang, Ding Zhao, Junqiang Xi +2
Personalized driver models play a key role in the development of advanced driver assistance systems and automated driving systems. Traditionally, physical-based driver models with…
Evaluation of Lane Departure Correction Systems Using a Stochastic Driver Model
Wenshuo Wang, Ding Zhao
Evaluating the effectiveness and benefits of driver assistance systems is crucial for improving the system performance. In this paper, we propose a novel framework for testing and…