Convolutional Neural Networks (CNNs) are a specialized class of deep neural networks tailored for processing high-dimensional data, excelling in tasks like image classification, object detection, and facial recognition. Their architecture is built on convolutional layers interspersed with...

Spatial econometrics deals with econometric modeling in the presence of spatial dependence and heterogeneity, where observations correspond to specific spatial units such as points or regions. Traditional estimation techniques assume independent observations and are inadequate when spatial...

This study applies a heteroscedastic spatial Durbin panel data model to investigate how sociodemographic and socioeconomic factors influence regional commuter mobility in the Greater Stockholm Area. Commuter mobility, defined as the flow of people to and from workplaces across regions and over...