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Macroscopic Traffic Flow Modeling with Physics Regularized Gaussian
  Process: A New Insight into Machine Learning Applications

Macroscopic Traffic Flow Modeling with Physics Regularized Gaussian Process: A New Insight into Machine Learning Applications

6 February 2020
Yun Yuan
X. Yang
Zhao Zhang
Shandian Zhe
    AI4CE
ArXivPDFHTML

Papers citing "Macroscopic Traffic Flow Modeling with Physics Regularized Gaussian Process: A New Insight into Machine Learning Applications"

11 / 11 papers shown
Title
Closed-Loop Neural Operator-Based Observer of Traffic Density
Closed-Loop Neural Operator-Based Observer of Traffic Density
Alice Harting
Karl H. Johansson
Matthieu Barreau
35
0
0
07 Apr 2025
MoGERNN: An Inductive Traffic Predictor for Unobserved Locations in Dynamic Sensing Networks
MoGERNN: An Inductive Traffic Predictor for Unobserved Locations in Dynamic Sensing Networks
Qishen Zhou
Yifan Zhang
Michail A. Makridis
Anastasios Kouvelas
Yibing Wang
Simon Hu
AI4TS
75
1
0
21 Jan 2025
Physics-informed Machine Learning for Calibrating Macroscopic Traffic
  Flow Models
Physics-informed Machine Learning for Calibrating Macroscopic Traffic Flow Models
Yu Tang
Li Jin
K. Ozbay
AI4CE
18
1
0
12 Jul 2023
Inverting the Fundamental Diagram and Forecasting Boundary Conditions:
  How Machine Learning Can Improve Macroscopic Models for Traffic Flow
Inverting the Fundamental Diagram and Forecasting Boundary Conditions: How Machine Learning Can Improve Macroscopic Models for Traffic Flow
Maya Briani
E. Cristiani
Elia Onofri
26
2
0
21 Mar 2023
Traffic State Estimation from Vehicle Trajectories with Anisotropic
  Gaussian Processes
Traffic State Estimation from Vehicle Trajectories with Anisotropic Gaussian Processes
Fan Wu
Zhanhong Cheng
Huiyu Chen
T. Qiu
Lijun Sun
27
3
0
04 Mar 2023
IDM-Follower: A Model-Informed Deep Learning Method for Long-Sequence
  Car-Following Trajectory Prediction
IDM-Follower: A Model-Informed Deep Learning Method for Long-Sequence Car-Following Trajectory Prediction
Yilin Wang
Yiheng Feng
36
5
0
20 Oct 2022
A Hybrid Physics Machine Learning Approach for Macroscopic Traffic State Estimation
Zhao Zhang
Ding Zhao
X. Yang
11
3
0
01 Feb 2022
Short-term traffic prediction using physics-aware neural networks
Short-term traffic prediction using physics-aware neural networks
M. Pereira
Annika Lang
Balázs Kulcsár
34
21
0
21 Sep 2021
A Physics-Informed Deep Learning Paradigm for Traffic State and
  Fundamental Diagram Estimation
A Physics-Informed Deep Learning Paradigm for Traffic State and Fundamental Diagram Estimation
Rongye Shi
Zhaobin Mo
Kuang Huang
Xuan Di
Qi Du
PINN
19
86
0
06 Jun 2021
Estimating Traffic Speeds using Probe Data: A Deep Neural Network
  Approach
Estimating Traffic Speeds using Probe Data: A Deep Neural Network Approach
Felix Rempe
P. Franeck
Klaus Bogenberger
3DV
18
2
0
19 Apr 2021
Bayesian Inference with Posterior Regularization and applications to
  Infinite Latent SVMs
Bayesian Inference with Posterior Regularization and applications to Infinite Latent SVMs
Jun Zhu
Ning Chen
Eric P. Xing
BDL
65
157
0
05 Oct 2012
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