21 citations · 21 across the 8 of their papers we have counts for
8 papers
TrajGPT: Controlled Synthetic Trajectory Generation Using a Multitask Transformer-Based Spatiotemporal Model
Shang-Ling Hsu, Emmanuel Tung, John Krumm +2
Human mobility modeling from GPS-trajectories and synthetic trajectory generation are crucial for various applications, such as urban planning, disaster management and epidemiology…
A System for Critical Facility and Resource Optimization in Disaster Management and Planning
Emmanuel Tung, Ali Mostafavi, Maoxu Li +3
Disruptions to medical infrastructure during disasters pose significant risks to critically ill patients with advanced chronic kidney disease or end-stage renal disease. To enhance…
Back to Bayesics: Uncovering Human Mobility Distributions and Anomalies with an Integrated Statistical and Neural Framework
Minxuan Duan, Yinlong Qian, Lingyi Zhao +4
Existing methods for anomaly detection often fall short due to their inability to handle the complexity, heterogeneity, and high dimensionality inherent in real-world mobility data…
Uncertainty-aware Human Mobility Modeling and Anomaly Detection
Haomin Wen, Shurui Cao, Zeeshan Rasheed +2
Given the temporal GPS coordinates from a large set of human agents, how can we model their mobility behavior toward effective anomaly (e.g. bad-actor or malicious behavior) detect…
NUMOSIM: A Synthetic Mobility Dataset with Anomaly Detection Benchmarks
Chris Stanford, Suman Adari, Xishun Liao +10
Collecting real-world mobility data is challenging. It is often fraught with privacy concerns, logistical difficulties, and inherent biases. Moreover, accurately annotating anomali…
Geo-Llama: Leveraging LLMs for Human Mobility Trajectory Generation with Spatiotemporal Constraints
Siyu Li, Toan Tran, Haowen Lin +5
Generating realistic human mobility data is essential for various application domains, including transportation, urban planning, and epidemic control, as real data is often inacces…
Learning Citywide Patterns of Life from Trajectory Monitoring
Mark Tenzer, Zeeshan Rasheed, Khurram Shafique
The recent proliferation of real-world human mobility datasets has catalyzed geospatial and transportation research in trajectory prediction, demand forecasting, travel time estima…
Meta-Learning over Time for Destination Prediction Tasks
Mark Tenzer, Zeeshan Rasheed, Khurram Shafique +1
A need to understand and predict vehicles' behavior underlies both public and private goals in the transportation domain, including urban planning and management, ride-sharing serv…