5 papers
Adaptive Domain Decomposition Physics-Informed Neural Networks for Traffic State Estimation with Sparse Sensor Data
Eunhan Ka, Ludovic Leclercq, Satish V. Ukkusuri
Traffic state estimation from sparse fixed sensors is challenging because physics-informed neural networks (PINNs) tend to over-smooth the shockwaves admitted by the Lighthill-Whit…
Stable GFlowNets with TV Monitoring and Probabilistic Guarantees
Zengxiang Lei, Ananth Shreekumar, Jonathan Rosenthal +6
Generative Flow Networks (GFlowNets) sample diverse structured objects in proportion to reward and have been applied to molecular discovery and biological-sequence design, where fi…
MoE-TransMov: A Transformer-based Model for Next POI Prediction in Familiar & Unfamiliar Movements
Ruichen Tan, Jiawei Xue, Kota Tsubouchi +2
Accurate prediction of the next point of interest (POI) within human mobility trajectories is essential for location-based services, as it enables more timely and personalized reco…
D4+: Emergent Adversarial Driving Maneuvers with Approximate Functional Optimization
Diego Ortiz Barbosa, Luis Burbano, Carlos Hernandez +4
Intelligent mechanisms implemented in autonomous vehicles, such as proactive driving assist and collision alerts, reduce traffic accidents. However, verifying their correct functio…
Data Mining in Transportation Networks with Graph Neural Networks: A Review and Outlook
Jiawei Xue, Ruichen Tan, Jianzhu Ma +1
Data mining in transportation networks (DMTNs) refers to using diverse types of spatio-temporal data for various transportation tasks, including pattern analysis, traffic predictio…