Pusan National University scientists develop robust “Huber mean” for geometric data
Peer-Reviewed Publication
Updates every hour. Last Updated: 23-Nov-2025 20:11 ET (24-Nov-2025 01:11 GMT/UTC)
In many modern sciences, data often exist on curved geometric spaces rather than flat planes, posing challenges for traditional statistical tools. These curved spaces are called Riemannian manifolds. Researchers from Pusan National University and Seoul National University have developed the “Huber mean,” a new method for robustly analyzing data on Riemannian manifolds. This study offers a powerful way to calculate averages that remain accurate even when data contain noise or outliers.
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