AI enables more effective humanitarian action by estimating population density
Researchers from EPFL and ETH Zurich, working together with the International Committee of the Red Cross (ICRC) and Bin Khalifa Unversity (Qatar), have developed a program that can generate population density estimates with unparalleled precision, and only needs a rough estimate at the regional level to learn.
Estimating the density of a distribution from samples is a fundamental problem in statistics. In many practical settings, the Wasserstein distance is an appropriate error metric for density estimation. For example, when estimating population densities in a geographic region, a small Wasserstein distance means that the estimate is able to…
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