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cs.LG2025★ 1 cited
Structure-preserving contrastive learning for spatial time series
Yiru Jiao, Sander van Cranenburgh, Simeon Calvert +1
The effectiveness of neural network models largely relies on learning meaningful latent patterns from data, where self-supervised learning of informative representations can enhanc…
cs.LG2023
Spatial and Temporal Characteristics of Freight Tours: A Data-Driven Exploratory Analysis
Ali Nadi, Lóránt Tavasszy, J. W. C. van Lint +1
This paper presents a modeling approach to infer scheduling and routing patterns from digital freight transport activity data for different freight markets. We provide a complete m…