FEI is a non-contrastive self-supervised method for time series that uses frequency masking prompts to infer embeddings, and it outperforms contrastive baselines in transfer tests.
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Frequency-Masked Embedding Inference: A Non-Contrastive Approach for Time Series Representation Learning
FEI is a non-contrastive self-supervised method for time series that uses frequency masking prompts to infer embeddings, and it outperforms contrastive baselines in transfer tests.