STEP embeds progressive time series into a manifold between orthogonal prototypes so that polar angle tracks irreversible state progression and radius tracks mode via self-supervised contrastive learning.
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STEP: Learning STructured Embeddings for Progressive Time Series
STEP embeds progressive time series into a manifold between orthogonal prototypes so that polar angle tracks irreversible state progression and radius tracks mode via self-supervised contrastive learning.