Using graph neural networks to measure the spatial homogeneity of road networks

Researchers at Purdue University and Peking University have recently carried out a study aimed at better understanding road networks in cities worldwide using machine-learning tools. Their paper, published in Nature Machine Intelligence, outlines the results of an in-depth, data-driven analysis of road map-related data captured in 30 cities worldwide.

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