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JEPA-Anything: Learning Predictive Models across Different Worlds
JEPA-Anything extends joint‑embedding predictive architectures with orthogonal predictive factorization, letting a single model learn complementary latent factors that can be recombined for prediction across disparate domains. The paper shows consistent performance gains on ten dynamics tasks, molecular simulations, and clinical event forecasting, plus experimental validation of a biologically‑de…
Hugging Face Daily Papersarxiv.org1 minpaper
