Multiscale Reconstruction of Weighted Networks from Coarse-Grained Data
Reconstructing detailed networks from only blurry, big-picture information
When researchers only have access to coarse data about a network—like trade flows between regions rather than between individual countries—they usually can't reliably figure out what the detailed network actually looks like. This paper shows a new method can reconstruct fine-scale networks from coarse information with high accuracy, even outperforming methods that have access to more detailed data during training.
Most real-world networks are only observed at rough levels of detail: governments track trade between countries or regions, not every individual transaction; companies report industry-level output, not product-by-product flows. This method means economists and analysts can now infer the hidden fine-grained structure of these networks without collecting expensive new data, making it possible to spot bottlenecks, vulnerabilities, and inefficiencies that coarse-grained views would miss.