Author

Jun-Yuan Liu

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#machine learning Preprint Aug 2026

Modelling daily activity patterns from mobile phone location data via deep representation learning

Passively collected mobile phone location data provide large-scale, longitudinal observations of human mobility but do not directly reveal activity purposes. The functional characteristics of visited locations offer useful contextual information, yet their relationship with activity purpose remains uncertain, particula...

Xing-Lei Wang, Jun-Yuan Liu, Guang-Sheng Dong et al. · 0 citations

#machine learning Preprint Aug 2026

LE4Mob: Towards Inductive, Distance-Aware and General-Purpose Location Embedding for Human Mobility Modelling

Location representations provide mobility models with fundamental information about the spatial position, functional characteristics, and relationships of places. However, existing embeddings are often dependent on mobility observations, unable to represent unseen locations, and weakly constrained to retain geographic...

Xing-Lei Wang, Stephen Law, Zi-Chao Zeng et al. · 0 citations

Preprint Aug 2026

From Urban Mobility to Epidemic Dynamics: A Mixture-of-Experts Framework with Preference Alignment for Policy Scenario Simulation

The results show that epidemic-activity conclusions depend on how policy calendars are translated into behavior, and that agent-level mobility-share modeling provides an interpretable bridge between policy timing, behavior, and downstream simulation.

Yunhai Ye, Arsalan Dezhkam, Jun-Yuan Liu et al. · 0 citations