TY - DATA
T1 - Data underlying the publication: Structure-preserving contrastive learning for spatial time series
PY - 2025/06/11
AU - Yiru Jiao
AU - Simeon Calvert
AU - Sander van Cranenburgh
AU - Hans van Lint
UR - 
DO - 10.4121/3b8cf098-c2ce-49b1-8e36-74b37872aaa6.v1
KW - Contrastive learning
KW - representation learning
KW - time series
KW - spatio-temporal data
KW - traffic interaction
N2 - <p>This dataset includes the resulting data of the research: Structure-preserving contrastive learning for spatial time series. It includes precomputed distance matrices, logs and results from hyperparameter grid search, trained encoder checkpoints, as well as evaluation metrics for UEA classification and traffic prediction tasks. The research is experimental and focuses on enhancing self-supervised contrastive learning by preserving fine‐grained spatio-temporal similarity structures. The proposed methods are applied to public UEA archive datasets of multivariate time series and specialised macro- and micro-traffic datasets. The scripts that produced these data are open-sourced at https://github.com/Yiru-Jiao/SPCLT</p>
ER -