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cs.MA2025
All Models Are Wrong, But Can They Be Useful? Lessons from COVID-19 Agent-Based Models: A Systematic Review
Emma Von Hoene, Sara Von Hoene, Szandra Peter +9
The COVID-19 pandemic prompted a surge in computational models to simulate disease dynamics and guide interventions. Agent-based models (ABMs) are well-suited to capture population…
cs.LG2025
PlaceRep: Geospatial Place Representation Learning from Large-Scale Point-of-Interest Data
Mohammad Hashemi, Hossein Amiri, Andreas Zufle
Learning effective representations of urban environments requires capturing spatial structure beyond fixed administrative boundaries. Existing geospatial representation learning ap…