4 papers
How Good Are Time-Series Foundation Models for Pedestrian Crowd Count Forecasting? A Cross-Dataset Comparative Study
Theivaprakasham Hari, Ziteng Li, Yanan Xin +2
Pedestrian-count forecasting supports pedestrian-oriented Intelligent Transportation Systems (ITS), including crowd monitoring, pedestrian-traffic staffing and routing, and proacti…
Towards Reliable Zero-Shot Crowd Forecasting: Evaluating Time Series Foundation Models for Special Event Pedestrian Forecasting
Ziteng Li, Yanan Xin, Tina Comes +1
Managing massive crowds during infrequent special events requires reliable real-time pedestrian-flow forecasting to ensure public safety and operational efficiency. However, superv…
Asymmetric Peak-Aware Loss for Peak-Critical Time Series Forecasting
Theivaprakasham Hari, Yanan Xin, Winnie Daamen +2
In many operational time-series forecasting applications, such as crowd demand forecasting, the risk related to under-prediction is substantially higher than that of over-predictio…
SORTeD Rashomon Sets of Sparse Decision Trees: Anytime Enumeration
Elif Arslan, Jacobus G. M. van der Linden, Serge Hoogendoorn +2
Sparse decision tree learning provides accurate and interpretable predictive models that are ideal for high-stakes applications by finding the single most accurate tree within a (s…