Deterministic Prediction as Global Velocity: Flow Matching for Probabilistic Time-Series Forecast

Accurate uncertainty quantification is critical for many time series forecasting applications, and recent studies have increasingly adopted generative models to capture predictive uncertainty. Existing approaches often combine deterministic forecasting with generative modeling to improve predictive