NormWear-2 encodes physiological signals and interventions into a shared latent space, models their joint evolution as a dynamical system, and uses chaos-theoretic balancing during pretraining to achieve superior multi-scale forecasting on diverse real-world datasets.
J.2 Weighted sum of normalized Shannon Entropy and Granularity
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Toward World Modeling of Physiological Signals with Chaos-Theoretic Balancing and Latent Dynamics
NormWear-2 encodes physiological signals and interventions into a shared latent space, models their joint evolution as a dynamical system, and uses chaos-theoretic balancing during pretraining to achieve superior multi-scale forecasting on diverse real-world datasets.