A package for online distributional learning.
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Updated
Jun 12, 2026 - Python
A package for online distributional learning.
Distributional crypto-return forecasting via Wasserstein-geodesic extrapolation in quantile-function space. WGeo family wins 12/12 (asset × horizon) cells over 6.75y walk-forward CRPS vs GARCH and classical baselines. v0.4.
Reference implementation: cluster-adaptive spatial bases + cluster-aware conformal calibration for spatio-temporal distributional prediction (DA-STDK).
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