Michael G. Rabbat

H-JEPA: End-to-End Learning of Hierarchical World Models for Visual Planning

Long-horizon planning with latent world models requires reasoning across timescales and levels of abstraction. Existing task-agnostic JEPA world models predict and plan at a single timescale or with multiple horizons in one shared latent space. We introduce H-JEPA, an end-to-end recipe for training a hierarchy of actio...