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Associate Professor
Supervisor of Doctorate Candidates

E-Mail:

Date of Employment:2023-01-16

School/Department:Institute of Artificial Intelligence

Education Level:博士研究生

Business Address:New Building B1007

Contact Information:shirongye@buaa.edu.cn

Alma Mater:Carnegie Mellon University

Rongye Shi

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Education Level:博士研究生

Alma Mater:Carnegie Mellon University

Paper

Current position: Home / Paper
Physics-Informed Deep Learning for Traffic State Estimation: A Hybrid Paradigm Informed By Second-Order Traffic Models

DOI number:10.1609/aaai.v35i1.16132
Journal:AAAI Conference on Artificial Intelligence
Co-author:Zhaobin Mo,Xuan Di
First Author:Rongye Shi
Indexed by:Essay collection
Document Type:C
Page Number:540-547
Translation or Not:no
Date of Publication:2021-05-18
Included Journals:EI