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2020 – today
- 2024
[c6]Zhaobin Mo, Yongjie Fu, Xuan Di:
PI-NeuGODE: Physics-Informed Graph Neural Ordinary Differential Equations for Spatiotemporal Trajectory Prediction. AAMAS 2024: 1418-1426- [c5]Yongjie Fu, Mehmet Kerem Türkcan
, Vikram Anantha, Zoran Kostic, Gil Zussman, Xuan Di:
Digital Twin for Pedestrian Safety Warning at a Single Urban Traffic Intersection. IV 2024: 2640-2645 - [i7]Boxuan Wang, Haonan Duan, Yanhao Feng, Xu Chen, Yongjie Fu, Zhaobin Mo, Xuan Di:
Can LLMs Understand Social Norms in Autonomous Driving Games? CoRR abs/2408.12680 (2024) - [i6]Yongjie Fu, Yunlong Li, Xuan Di:
GenDDS: Generating Diverse Driving Video Scenarios with Prompt-to-Video Generative Model. CoRR abs/2408.15868 (2024) - [i5]Yongjie Fu, Anmol Jain, Xuan Di, Xu Chen, Zhaobin Mo:
DriveGenVLM: Real-world Video Generation for Vision Language Model based Autonomous Driving. CoRR abs/2408.16647 (2024) - 2023
- [j4]Xuan Di, Rongye Shi, Zhaobin Mo, Yongjie Fu:
Physics-Informed Deep Learning for Traffic State Estimation: A Survey and the Outlook. Algorithms 16(6): 305 (2023) - [j3]Xuan Di, Yiqiao Yin, Yongjie Fu, Zhaobin Mo, Shaw-Hwa Lo, Carolyn DiGuiseppi, David W. Eby, Linda L. Hill, Thelma J. Mielenz, David Strogatz, Minjae Kim, Guohua Li:
Detecting mild cognitive impairment and dementia in older adults using naturalistic driving data and interaction-based classification from influence score. Artif. Intell. Medicine 138: 102510 (2023) - [j2]Yongjie Fu, Dazhi Zhang, Yunlong Xiao, Zhihui Wang, Huabing Zhou:
An Interpretable Time Series Data Prediction Framework for Severe Accidents in Nuclear Power Plants. Entropy 25(8): 1160 (2023) - [c4]Yongjie Fu, Xuan Di:
Federated Reinforcement Learning for Adaptive Traffic Signal Control: A Case Study in New York City. ITSC 2023: 5738-5743 - [i4]Xuan Di, Rongye Shi, Zhaobin Mo, Yongjie Fu:
Physics-Informed Deep Learning For Traffic State Estimation: A Survey and the Outlook. CoRR abs/2303.02063 (2023) - 2022
- [c3]Zhaobin Mo, Yongjie Fu, Xuan Di:
Quantifying Uncertainty In Traffic State Estimation Using Generative Adversarial Networks. ITSC 2022: 2769-2774 - [c2]Shuo Liu, Yunhao Wang, Xu Chen, Yongjie Fu, Xuan Di:
SMART-eFlo: An Integrated SUMO-Gym Framework for Multi-Agent Reinforcement Learning in Electric Fleet Management Problem. ITSC 2022: 3026-3031 - [c1]Zhaobin Mo, Yongjie Fu, Daran Xu, Xuan Di:
TrafficFlowGAN: Physics-Informed Flow Based Generative Adversarial Network for Uncertainty Quantification. ECML/PKDD (3) 2022: 323-339 - [i3]Zhaobin Mo, Yongjie Fu, Daran Xu, Xuan Di:
TrafficFlowGAN: Physics-informed Flow based Generative Adversarial Network for Uncertainty Quantification. CoRR abs/2206.09319 (2022) - [i2]Zhaobin Mo, Yongjie Fu, Xuan Di:
Quantifying Uncertainty In Traffic State Estimation Using Generative Adversarial Networks. CoRR abs/2206.09349 (2022) - 2021
- [j1]Hailiang Lu, Hao Li, Yayun Cheng, Dong Zhu, Yinan Li, Pengju Dang, Rongchuan Lv, Rui Yu, Yongjie Fu:
An L-Band Phased Array Radiometer for Sea Surface Salinity in Coastal Zones. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 14: 1520-1531 (2021) - [i1]Wangzhi Li, Yaxing Cai, Ujwal Dinesha, Yongjie Fu, Xuan Di:
CVLight: Deep Reinforcement Learning for Adaptive Traffic Signal Control with Connected Vehicles. CoRR abs/2104.10340 (2021)
Coauthor Index
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