Xuan Di

Orcid: 0000-0003-2925-7697

According to our database1, Xuan Di authored at least 56 papers between 2018 and 2024.

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Bibliography

2024
InfoSTGCAN: An Information-Maximizing Spatial-Temporal Graph Convolutional Attention Network for Heterogeneous Human Trajectory Prediction.
Comput., June, 2024

Physics-Informed Graph Neural Operator for Mean Field Games on Graph: A Scalable Learning Approach.
Games, April, 2024

Mobility Pattern Analysis during Russia-Ukraine War Using Twitter Location Data.
Inf., February, 2024

DriveGenVLM: Real-world Video Generation for Vision Language Model based Autonomous Driving.
CoRR, 2024

GenDDS: Generating Diverse Driving Video Scenarios with Prompt-to-Video Generative Model.
CoRR, 2024

Can LLMs Understand Social Norms in Autonomous Driving Games?
CoRR, 2024

Stochastic Semi-Gradient Descent for Learning Mean Field Games with Population-Aware Function Approximation.
CoRR, 2024

TraveLLM: Could you plan my new public transit route in face of a network disruption?
CoRR, 2024

Learn to Tour: Operator Design For Solution Feasibility Mapping in Pickup-and-delivery Traveling Salesman Problem.
CoRR, 2024

Digital Twin for Pedestrian Safety Warning at a Single Urban Traffic Intersection.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2024

Graphon Mean Field Games with a Representative Player: Analysis and Learning Algorithm.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

SLAMuZero: Plan and Learn to Map for Joint SLAM and Navigation.
Proceedings of the Thirty-Fourth International Conference on Automated Planning and Scheduling, 2024

A Single Online Agent Can Efficiently Learn Mean Field Games.
Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 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

Sentiment Analysis on Multimodal Transportation during the COVID-19 Using Social Media Data.
Inf., February, 2023

Robust Data Sampling in Machine Learning: A Game-Theoretic Framework for Training and Validation Data Selection.
Games, February, 2023

Social Learning for Sequential Driving Dilemmas.
Games, 2023

Systemic reliability of bridge networks with mobile sensing-based model updating for postevent transportation decisions.
Comput. Aided Civ. Infrastructure Eng., 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

Federated Reinforcement Learning for Adaptive Traffic Signal Control: A Case Study in New York City.
Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2023

Whose Attitudes Toward Transit Are Most Affected by Rising Subway Crimes in New York City?
Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2023

Causal Imitation Learning via Inverse Reinforcement Learning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Learning Dual Mean Field Games on Graphs.
Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023

A Hybrid Framework of Reinforcement Learning and Physics-Informed Deep Learning for Spatiotemporal Mean Field Games.
Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

2022
A Physics-Informed Deep Learning Paradigm for Traffic State and Fundamental Diagram Estimation.
IEEE Trans. Intell. Transp. Syst., 2022

A Unified Network Equilibrium for E-Hailing Platform Operation and Customer Mode Choice.
CoRR, 2022

TrafficFlowGAN: Physics-Informed Flow Based Generative Adversarial Network for Uncertainty Quantification.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

Social Learning In Markov Games: Empowering Autonomous Driving.
Proceedings of the 2022 IEEE Intelligent Vehicles Symposium, 2022

Bayesian Optimization for Multi-Agent Routing in Markov Games.
Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2022

Quantifying Uncertainty In Traffic State Estimation Using Generative Adversarial Networks.
Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2022

SMART-eFlo: An Integrated SUMO-Gym Framework for Multi-Agent Reinforcement Learning in Electric Fleet Management Problem.
Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2022

How the COVID-19 Pandemic Influences Human Mobility? Similarity Analysis Leveraging Social Media Data.
Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2022

Learning Human Driving Behaviors with Sequential Causal Imitation Learning.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
A Physics-Informed Deep Learning Paradigm for Traffic State Estimation and Fundamental Diagram Discovery.
CoRR, 2021

CVLight: Deep Reinforcement Learning for Adaptive Traffic Signal Control with Connected Vehicles.
CoRR, 2021

Physics-Informed Deep Learning for Traffic State Estimation.
CoRR, 2021

Sentiment Analysis of Autonomous Vehicles After Extreme Events Using Social Media Data.
Proceedings of the 24th IEEE International Intelligent Transportation Systems Conference, 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
A restricted path-based ridesharing user equilibrium.
J. Intell. Transp. Syst., 2020

A Physics-Informed Deep Learning Paradigm for Car-Following Models.
CoRR, 2020

Driving and Routing Game for Autonomous Vehicles on a Network.
CoRR, 2020

Multi-Agent Reinforcement Learning for Dynamic Routing Games: A Unified Paradigm.
CoRR, 2020

A Survey on Autonomous Vehicle Control in the Era of Mixed-Autonomy: From Physics-Based to AI-Guided Driving Policy Learning.
CoRR, 2020

When Do Drivers Concentrate? Attention-based Driver Behavior Modeling With Deep Reinforcement Learning.
CoRR, 2020

Reward Design for Driver Repositioning Using Multi-Agent Reinforcement Learning.
CoRR, 2020

An LSTM-Based Autonomous Driving Model Using Waymo Open Dataset.
CoRR, 2020

Long-Term Prediction of Lane Change Maneuver Through a Multilayer Perceptron.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2020

Similarity Analysis of Spatial-Temporal Mobility Patterns for Travel Mode Prediction Using Twitter Data.
Proceedings of the 23rd IEEE International Conference on Intelligent Transportation Systems, 2020

2019
A Similitude Theory for Modeling Traffic Flow Dynamics.
IEEE Trans. Intell. Transp. Syst., 2019

Liability Design for Autonomous Vehicles and Human-Driven Vehicles: A Hierarchical Game-Theoretic Approach.
CoRR, 2019

Where to Find Next Passengers on E-hailing Platforms? - A Markov Decision Process Approach.
CoRR, 2019

A Game-Theoretic Framework for Autonomous Vehicles Velocity Control: Bridging Microscopic Differential Games and Macroscopic Mean Field Games.
CoRR, 2019

Stabilizing Traffic via Autonomous Vehicles: A Continuum Mean Field Game Approach.
Proceedings of the 2019 IEEE Intelligent Transportation Systems Conference, 2019

2018
Multimodal Connections between Dockless Bikesharing and Ride-Hailing: An Empirical Study in New York City.
Proceedings of the 21st International Conference on Intelligent Transportation Systems, 2018

Large-scale short-term urban taxi demand forecasting using deep learning.
Proceedings of the 23rd Asia and South Pacific Design Automation Conference, 2018


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