2 papers
cs.LG2025
Black box behavioural modelling: Predicting human activity schedules with a deep conditional generative approach
Fred Shone, Tim Hillel
Modelling the complexity and diversity of human activity scheduling behaviour is inherently challenging. We demonstrate ActVAE, a deep conditional-generative machine learning appro…
cs.LG2025
Synthesising Activity Participations and Scheduling with Deep Generative Machine Learning
Fred Shone, Tim Hillel
Using a deep generative machine learning approach, we synthesise human activity participations and scheduling; i.e. the choices of what activities to participate in and when. Activ…