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Adam Cataldo

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#machine learning Preprint Sep 2026

Halo: Improving forecast accuracy through heteroscedastic estimation

Halo is a modification that reuses an existing deep forecaster's architecture, giving it a second output for the scale of its implied distribution and training it under the matching negative log likelihood, and shows it improves the point estimate, in contrast to reported negative results for heteroscedastic estimation...

Adam Cataldo · 0 citations