3 papers
stat.AP2026
A Bayesian Framework for Post-disruption Travel Time Prediction in Metro Networks
Shayan Nazemi, Aurélie Labbe, Stefan Steiner +3
Disruptions are an inherent feature of transportation systems, occurring unpredictably and with varying durations. Even after an incident is reported as resolved, disruptions can i…
stat.ME2025
Scalable Spatiotemporal Modeling for Bicycle Count Prediction
Rishikesh Yadav, Alexandra M. Schmidt, Aurelie Labbe +2
We propose a novel sparse spatiotemporal dynamic generalized linear model for efficient inference and prediction of bicycle count data. Assuming Poisson distributed counts with spa…
stat.ME2025
A Robust Nonparametric Framework for Detecting Repeated Spatial Patterns
Rajitha Senanayake, Pratheepa Jeganathan
Identifying spatially contiguous clusters and repeated spatial patterns (RSP) characterized by similar underlying distributions that are spatially apart is a key challenge in moder…