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DisTreebution was initiated at the Swiss Data Science Center (SDSC) at EPFL to build practical, open tools for rigorous uncertainty quantification and distributional prediction. The project aims to deliver tree-based scalable algorithms, reproducible workflows and clear evaluation metrics so practitioners can deploy models that communicate uncertainty reliably.