A small DDPM built from scratch, generating a distribution of next-month temperature anomalies instead of one point estimate. Calibration is reasonable, close to an 80% coverage target. The central prediction overreacts to its input, losing to a linear baseline. A fix attempt made this worse, not better, reported directly.
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Updated
Aug 6, 2026 - Jupyter Notebook