This paper exposes problems of the commonly used technique of splitting the available data in neural spatial interaction modelling into training, validation, and test sets that are held fixed and warns about drawing too strong conclusions from such static splits. Using a bootstrapping procedure,...

This paper investigates the impact of knowledge capital stocks on total factor productivity through the lens of the knowledge capital model proposed by Griliches (1979), augmented with a spatially discounted cross-region knowledge spillover pool variable. The objective is to shift attention from...

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...