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2020 – today
- 2025
[i32]Zhaobin Mo, Haotian Xiang, Xuan Di:
diffIRM: A Diffusion-Augmented Invariant Risk Minimization Framework for Spatiotemporal Prediction over Graphs. CoRR abs/2501.00305 (2025)- [i31]Zhaobin Mo, Yunlong Li, Xuan Di:
SafeAug: Safety-Critical Driving Data Augmentation from Naturalistic Datasets. CoRR abs/2501.02143 (2025) - [i30]Xuan Di, Yongjie Fu, Mehmet Kerem Türkcan, Mahshid Ghasemi, Zhaobin Mo, Chengbo Zang, Abhishek Adhikari, Zoran Kostic, Gil Zussman:
AI-Powered Urban Transportation Digital Twin: Methods and Applications. CoRR abs/2501.10396 (2025) - 2024
- [j14]Kangrui Ruan
, Xuan Di:
InfoSTGCAN: An Information-Maximizing Spatial-Temporal Graph Convolutional Attention Network for Heterogeneous Human Trajectory Prediction. Comput. 13(6): 151 (2024) - [j13]Xu Chen, Shuo Liu, Xuan Di:
Physics-Informed Graph Neural Operator for Mean Field Games on Graph: A Scalable Learning Approach. Games 15(2): 12 (2024) - [j12]Yupei Shu, Xu Chen, Xuan Di:
Mobility Pattern Analysis during Russia-Ukraine War Using Twitter Location Data. Inf. 15(2): 76 (2024) - [j11]Zhaobin Mo, Xu Chen, Xuan Di, Elisa Iacomini, Chiara Segala, Michael Herty, Mathieu Laurière:
A Game-Theoretic Framework for Generic Second-Order Traffic Flow Models Using Mean Field Games and Adversarial Inverse Reinforcement Learning. Transp. Sci. 58(6): 1403-1426 (2024) - [j10]Zhaobin Mo, Haotian Xiang, Xuan Di:
Cross- and Context-Aware Attention Based Spatial-Temporal Graph Convolutional Networks for Human Mobility Prediction. ACM Trans. Spatial Algorithms Syst. 10(4): 1-25 (2024) - [c25]Zhaobin Mo, Yongjie Fu, Xuan Di:
PI-NeuGODE: Physics-Informed Graph Neural Ordinary Differential Equations for Spatiotemporal Trajectory Prediction. AAMAS 2024: 1418-1426 - [c24]Chenyu Zhang, Xu Chen, Xuan Di:
A Single Online Agent Can Efficiently Learn Mean Field Games. ECAI 2024: 3557-3564 - [c23]Bowen Fang, Xu Chen, Zhengkun Pan, Xuan Di:
SLAMuZero: Plan and Learn to Map for Joint SLAM and Navigation. ICAPS 2024: 196-200 - [c22]Fuzhong Zhou, Chenyu Zhang, Xu Chen, Xuan Di:
Graphon Mean Field Games with a Representative Player: Analysis and Learning Algorithm. ICML 2024 - [c21]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 - [c20]Kangrui Ruan, Junzhe Zhang, Xuan Di, Elias Bareinboim:
Causal Imitation for Markov Decision Processes: a Partial Identification Approach. NeurIPS 2024 - [i29]Bowen Fang, Xu Chen, Xuan Di:
Learn to Tour: Operator Design For Solution Feasibility Mapping in Pickup-and-delivery Traveling Salesman Problem. CoRR abs/2404.11458 (2024) - [i28]Chenyu Zhang, Xu Chen, Xuan Di:
A Single Online Agent Can Efficiently Learn Mean Field Games. CoRR abs/2405.03718 (2024) - [i27]Fuzhong Zhou, Chenyu Zhang, Xu Chen, Xuan Di:
Graphon Mean Field Games with a Representative Player: Analysis and Learning Algorithm. CoRR abs/2405.08005 (2024) - [i26]Bowen Fang, Zixiao Yang, Shukai Wang, Xuan Di:
TraveLLM: Could you plan my new public transit route in face of a network disruption? CoRR abs/2407.14926 (2024) - [i25]Chenyu Zhang, Xu Chen, Xuan Di:
Stochastic Semi-Gradient Descent for Learning Mean Field Games with Population-Aware Function Approximation. CoRR abs/2408.08192 (2024) - [i24]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) - [i23]Yongjie Fu, Yunlong Li, Xuan Di:
GenDDS: Generating Diverse Driving Video Scenarios with Prompt-to-Video Generative Model. CoRR abs/2408.15868 (2024) - [i22]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) - [i21]Kangrui Ruan, Xinyang Wang, Xuan Di:
From Twitter to Reasoner: Understand Mobility Travel Modes and Sentiment Using Large Language Models. CoRR abs/2411.02666 (2024) - [i20]Zhaobin Mo, Qingyuan Liu, Baohua Yan, Longxiang Zhang, Xuan Di:
Causal Adjacency Learning for Spatiotemporal Prediction Over Graphs. CoRR abs/2411.16142 (2024) - 2023
- [j9]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) - [j8]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) - [j7]Ekin Ozer, Arman Malekloo, Wasim Ramadan, Thanh T. X. Tran, Xuan Di:
Systemic reliability of bridge networks with mobile sensing-based model updating for postevent transportation decisions. Comput. Aided Civ. Infrastructure Eng. 38(8): 975-999 (2023) - [j6]Zhaobin Mo, Xuan Di, Rongye Shi:
Robust Data Sampling in Machine Learning: A Game-Theoretic Framework for Training and Validation Data Selection. Games 14(1): 13 (2023) - [j5]Xu Chen, Xuan Di, Zechu Li:
Social Learning for Sequential Driving Dilemmas. Games 14(3): 41 (2023) - [j4]Xu Chen, Zihe Wang, Xuan Di:
Sentiment Analysis on Multimodal Transportation during the COVID-19 Using Social Media Data. Inf. 14(2): 113 (2023) - [c19]Xu Chen, Shuo Liu, Xuan Di:
A Hybrid Framework of Reinforcement Learning and Physics-Informed Deep Learning for Spatiotemporal Mean Field Games. AAMAS 2023: 1079-1087 - [c18]Xu Chen, Shuo Liu, Xuan Di:
Learning Dual Mean Field Games on Graphs. ECAI 2023: 421-428 - [c17]Kangrui Ruan, Junzhe Zhang, Xuan Di, Elias Bareinboim:
Causal Imitation Learning via Inverse Reinforcement Learning. ICLR 2023 - [c16]Xu Chen, Yishi Wang, Xuan Di:
Whose Attitudes Toward Transit Are Most Affected by Rising Subway Crimes in New York City? ITSC 2023: 4153-4158 - [c15]Yongjie Fu, Xuan Di:
Federated Reinforcement Learning for Adaptive Traffic Signal Control: A Case Study in New York City. ITSC 2023: 5738-5743 - [i19]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
- [j3]Rongye Shi, Zhaobin Mo, Kuang Huang, Xuan Di, Qiang Du:
A Physics-Informed Deep Learning Paradigm for Traffic State and Fundamental Diagram Estimation. IEEE Trans. Intell. Transp. Syst. 23(8): 11688-11698 (2022) - [c14]Kangrui Ruan, Xuan Di:
Learning Human Driving Behaviors with Sequential Causal Imitation Learning. AAAI 2022: 4583-4592 - [c13]Zhaobin Mo, Yongjie Fu, Xuan Di:
Quantifying Uncertainty In Traffic State Estimation Using Generative Adversarial Networks. ITSC 2022: 2769-2774 - [c12]Xu Chen, Xuan Di:
How the COVID-19 Pandemic Influences Human Mobility? Similarity Analysis Leveraging Social Media Data. ITSC 2022: 2955-2960 - [c11]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 - [c10]Zhenyu Shou, Xu Chen, Xuan Di:
Bayesian Optimization for Multi-Agent Routing in Markov Games. ITSC 2022: 3993-3998 - [c9]Xu Chen, Zechu Li, Xuan Di:
Social Learning In Markov Games: Empowering Autonomous Driving. IV 2022: 478-483 - [c8]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 - [i18]Xu Chen, Xuan Di:
A Unified Network Equilibrium for E-Hailing Platform Operation and Customer Mode Choice. CoRR abs/2203.04865 (2022) - [i17]Zhaobin Mo, Yongjie Fu, Daran Xu, Xuan Di:
TrafficFlowGAN: Physics-informed Flow based Generative Adversarial Network for Uncertainty Quantification. CoRR abs/2206.09319 (2022) - [i16]Zhaobin Mo, Yongjie Fu, Xuan Di:
Quantifying Uncertainty In Traffic State Estimation Using Generative Adversarial Networks. CoRR abs/2206.09349 (2022) - 2021
- [c7]Rongye Shi, Zhaobin Mo, Xuan Di:
Physics-Informed Deep Learning for Traffic State Estimation: A Hybrid Paradigm Informed By Second-Order Traffic Models. AAAI 2021: 540-547 - [c6]Xu Chen, Haohan Zeng, Heng Xu, Xuan Di:
Sentiment Analysis of Autonomous Vehicles After Extreme Events Using Social Media Data. ITSC 2021: 1211-1216 - [i15]Rongye Shi, Zhaobin Mo, Kuang Huang, Xuan Di, Qiang Du:
Physics-Informed Deep Learning for Traffic State Estimation. CoRR abs/2101.06580 (2021) - [i14]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) - [i13]Rongye Shi, Zhaobin Mo, Kuang Huang, Xuan Di, Qiang Du:
A Physics-Informed Deep Learning Paradigm for Traffic State Estimation and Fundamental Diagram Discovery. CoRR abs/2106.03142 (2021) - 2020
- [j2]Meng Li, Xuan Di, Henry X. Liu, Hai-Jun Huang:
A restricted path-based ridesharing user equilibrium. J. Intell. Transp. Syst. 24(4): 383-403 (2020) - [c5]Zhenyu Shou, Zhenhao Cao, Xuan Di:
Similarity Analysis of Spatial-Temporal Mobility Patterns for Travel Mode Prediction Using Twitter Data. ITSC 2020: 1-6 - [c4]Zhenyu Shou, Ziran Wang, Kyungtae Han, Yongkang Liu, Prashant Tiwari, Xuan Di:
Long-Term Prediction of Lane Change Maneuver Through a Multilayer Perceptron. IV 2020: 246-252 - [i12]Zhicheng Li, Zhihao Gu, Xuan Di, Rongye Shi:
An LSTM-Based Autonomous Driving Model Using Waymo Open Dataset. CoRR abs/2002.05878 (2020) - [i11]Zhenyu Shou, Xuan Di:
Reward Design for Driver Repositioning Using Multi-Agent Reinforcement Learning. CoRR abs/2002.06723 (2020) - [i10]Xingbo Fu, Xuan Di, Zhaobin Mo:
When Do Drivers Concentrate? Attention-based Driver Behavior Modeling With Deep Reinforcement Learning. CoRR abs/2002.11385 (2020) - [i9]Zhenyu Shou, Ziran Wang, Kyungtae Han, Yongkang Liu, Prashant Tiwari, Xuan Di:
Long-Term Prediction of Lane Change Maneuver Through a Multilayer Perceptron. CoRR abs/2006.12769 (2020) - [i8]Xuan Di, Rongye Shi:
A Survey on Autonomous Vehicle Control in the Era of Mixed-Autonomy: From Physics-Based to AI-Guided Driving Policy Learning. CoRR abs/2007.05156 (2020) - [i7]Zhenyu Shou, Xuan Di:
Multi-Agent Reinforcement Learning for Dynamic Routing Games: A Unified Paradigm. CoRR abs/2011.10915 (2020) - [i6]Kuang Huang, Xu Chen, Xuan Di, Qiang Du:
Driving and Routing Game for Autonomous Vehicles on a Network. CoRR abs/2012.08388 (2020) - [i5]Zhaobin Mo, Xuan Di, Rongye Shi:
A Physics-Informed Deep Learning Paradigm for Car-Following Models. CoRR abs/2012.13376 (2020)
2010 – 2019
- 2019
- [j1]Xuan Di, Yan Zhao, Shihong Ed Huang, Henry X. Liu:
A Similitude Theory for Modeling Traffic Flow Dynamics. IEEE Trans. Intell. Transp. Syst. 20(3): 900-911 (2019) - [c3]Kuang Huang, Xuan Di, Qiang Du, Xi Chen:
Stabilizing Traffic via Autonomous Vehicles: A Continuum Mean Field Game Approach. ITSC 2019: 3269-3274 - [i4]Kuang Huang, Xuan Di, Qiang Du, Xi Chen:
A Game-Theoretic Framework for Autonomous Vehicles Velocity Control: Bridging Microscopic Differential Games and Macroscopic Mean Field Games. CoRR abs/1903.06053 (2019) - [i3]Zhenyu Shou, Xuan Di, Jieping Ye, Hongtu Zhu, Robert C. Hampshire:
Where to Find Next Passengers on E-hailing Platforms? - A Markov Decision Process Approach. CoRR abs/1905.09906 (2019) - [i2]Kuang Huang, Xuan Di, Qiang Du, Xi Chen:
Stabilizing Traffic via Autonomous Vehicles: A Continuum Mean Field Game Approach. CoRR abs/1906.01554 (2019) - [i1]Xuan Di, Xu Chen, Eric Talley:
Liability Design for Autonomous Vehicles and Human-Driven Vehicles: A Hierarchical Game-Theoretic Approach. CoRR abs/1911.02405 (2019) - 2018
- [c2]Siyu Liao, Liutong Zhou, Xuan Di, Bo Yuan, Jinjun Xiong:
Large-scale short-term urban taxi demand forecasting using deep learning. ASP-DAC 2018: 428-433 - [c1]Qi Luo, Xuechun Dou, Xuan Di, Robert Cornelius Hampshire:
Multimodal Connections between Dockless Bikesharing and Ride-Hailing: An Empirical Study in New York City. ITSC 2018: 2256-2261
Coauthor Index
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