Regime-Aware Incremental Forecasting

Overview

A research project on incremental time-series forecasting that detects distributional regimes and reuses model checkpoints when patterns recur. The goal is to reduce retraining cost while preserving accuracy.

Scope (High Level)

• Regime feature extraction and similarity matching.
• Checkpoint reuse for efficient updates.
• Adaptive training when novel regimes appear.

Status

Research in progress. Preprint and open-source release are pending.