Zhaobin Mo
Orcid: 0000-0002-0465-8550
According to our database1,
Zhaobin Mo
authored at least 23 papers
between 2018 and 2025.
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Collaborative distances:
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Bibliography
2025
diffIRM: A Diffusion-Augmented Invariant Risk Minimization Framework for Spatiotemporal Prediction over Graphs.
CoRR, January, 2025
2024
Cross- and Context-Aware Attention Based Spatial-Temporal Graph Convolutional Networks for Human Mobility Prediction.
ACM Trans. Spatial Algorithms Syst., 2024
A Game-Theoretic Framework for Generic Second-Order Traffic Flow Models Using Mean Field Games and Adversarial Inverse Reinforcement Learning.
Transp. Sci., 2024
DriveGenVLM: Real-world Video Generation for Vision Language Model based Autonomous Driving.
CoRR, 2024
PI-NeuGODE: Physics-Informed Graph Neural Ordinary Differential Equations for Spatiotemporal Trajectory Prediction.
Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024
2023
Physics-Informed Deep Learning for Traffic State Estimation: A Survey and the Outlook.
Algorithms, June, 2023
Robust Data Sampling in Machine Learning: A Game-Theoretic Framework for Training and Validation Data Selection.
Games, February, 2023
Detecting mild cognitive impairment and dementia in older adults using naturalistic driving data and interaction-based classification from influence score.
Artif. Intell. Medicine, 2023
2022
A Physics-Informed Deep Learning Paradigm for Traffic State and Fundamental Diagram Estimation.
IEEE Trans. Intell. Transp. Syst., 2022
TrafficFlowGAN: Physics-Informed Flow Based Generative Adversarial Network for Uncertainty Quantification.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022
Quantifying Uncertainty In Traffic State Estimation Using Generative Adversarial Networks.
Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2022
2021
A Physics-Informed Deep Learning Paradigm for Traffic State Estimation and Fundamental Diagram Discovery.
CoRR, 2021
Physics-Informed Deep Learning for Traffic State Estimation: A Hybrid Paradigm Informed By Second-Order Traffic Models.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021
2020
When Do Drivers Concentrate? Attention-based Driver Behavior Modeling With Deep Reinforcement Learning.
CoRR, 2020
2018
CoRR, 2018
CoRR, 2018
Proceedings of the 2018 IEEE Intelligent Vehicles Symposium, 2018
Proceedings of the 2018 IEEE International Conference on Multimedia & Expo Workshops, 2018