3 papers
stat.ME2026
Incomplete Matrix Regression
Khaled Fouda, Aurélie Labbe, Karim Oualkacha
Matrix completion seeks to recover a low-rank matrix from a sparse and noisy subset of its entries. In many applications, such as recommendation systems and urban mobility, the obs…
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…