Modeling human mobility is key for urban planning, sustainability, public health, and economic development. The authors show that simple machine-learned closed-form models are as predictive of mobility flows as complex machine learning models, perform well in extrapolation, work across datasets and scales, and are gravity-like and thus interpretable.
- Oriol Cabanas-Tirapu
- Lluís Danús
- Roger Guimerà
