Sub-JEPA stabilizes JEPA-based world models by enforcing isotropic Gaussian priors in random subspaces, achieving better bias-variance balance and outperforming LeWM on continuous control tasks.
Sliced and Radon Wasserstein Barycenters of Measures.Journal of Mathematical Imaging and Vision, 51(1):22–45, January 2015
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Sub-JEPA: Subspace Gaussian Regularization for Stable End-to-End World Models
Sub-JEPA stabilizes JEPA-based world models by enforcing isotropic Gaussian priors in random subspaces, achieving better bias-variance balance and outperforming LeWM on continuous control tasks.