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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.AP2023
An utopic adventure in the modelling of conditional univariate and multivariate extremes
Léo R. Belzile, Arnab Hazra, Rishikesh Yadav
The EVA 2023 data competition consisted of four challenges, ranging from interval estimation for very high quantiles of univariate extremes conditional on covariates, point estimat…