Distribution-to-Distribution Neural Forecasting
Distribution-to-Distribution Neural Forecasting
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A neural framework that learns and recursively propagates predictive probability distributions directly, rather than sampling ensembles.
Why It Matters
This is the core novel paradigm proposed by the paper, shifting forecasting from trajectory-based to distribution-based evolution.
Evidence
A distribution-to-distribution (D2D) neural probabilistic forecasting framework is developed to operate directly on predictive distributions.
Related Papers
Metadata & Links
- created_at
- 2026-03-29T06:06:59Z