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TrafficFlowGAN: Physics-informed Flow based Generative Adversarial
  Network for Uncertainty Quantification

TrafficFlowGAN: Physics-informed Flow based Generative Adversarial Network for Uncertainty Quantification

19 June 2022
Zhaobin Mo
Yongjie Fu
Daran Xu
Xuan Di
    AI4CE
ArXivPDFHTML

Papers citing "TrafficFlowGAN: Physics-informed Flow based Generative Adversarial Network for Uncertainty Quantification"

3 / 3 papers shown
Title
AI-Powered Urban Transportation Digital Twin: Methods and Applications
AI-Powered Urban Transportation Digital Twin: Methods and Applications
Xuan Di
Yongjie Fu
Mehmet K.Turkcan
Mahshid Ghasemi
Zhaobin Mo
Chengbo Zang
Abhishek Adhikari
Z. Kostić
Gil Zussman
AI4CE
39
0
0
30 Dec 2024
Knowledge-data fusion oriented traffic state estimation: A stochastic
  physics-informed deep learning approach
Knowledge-data fusion oriented traffic state estimation: A stochastic physics-informed deep learning approach
Ting Wang
Ye Li
Rongjun Cheng
Guojian Zou
Takao Dantsujic
Dong Ngoduy
32
2
0
01 Sep 2024
Physics-Informed Deep Learning For Traffic State Estimation: A Survey
  and the Outlook
Physics-Informed Deep Learning For Traffic State Estimation: A Survey and the Outlook
Xuan Di
Rongye Shi
Zhaobin Mo
Yongjie Fu
PINN
AI4TS
AI4CE
29
28
0
03 Mar 2023
1