Romina Yalovetzky
@RominaYalov
Physicist bringing ideas from physics to computation: quantum & AI/ML. 10+ yrs in tech. Lead Applied Researcher @JPMorgan. MSc CS @NYUCourant (Fall ‘26).
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Can a JEPA world model provably avoid contraction and merging of latent states over long rollouts?
Unconstrained autoregressive predictors may contract the latent distribution. Our Symplectic Hamiltonian JEPA (LeHami) replaces the predictor with an action-conditioned Hamiltonian flow over a latent state (q, p), integrated with an exactly symplectic leapfrog step.
Volume is preserved at every rollout step, independently of the learned parameters or action sequence.
With @randall_balestriero @ylecun
Paper:
Website:
Code:
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