Generative trajectory forecasting is now practical: PathFM generates full multivariate paths in near-quantile-model speed, enabling better predictions of trajectory-dependent quantities like cumulative demand and peak timing.
PathFM is a time series forecasting model that generates complete future trajectories rather than just point predictions. Using flow matching, it can produce multiple realistic paths for a single series almost as fast as traditional quantile models, while better capturing dependencies between variables that matter for real-world applications like peak load prediction.