ShiFT uses deterministic temporal shifts to enforce shift invariance in contrastive learning, achieving state-of-the-art time series classification on six benchmarks plus UCR/UEA archives while cutting training time.
In: Proceedings of the European Conference on Artificial Intelligence (ECAI)
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Learning by Shifting: Temporal View Construction for Time Series Contrastive Learning
ShiFT uses deterministic temporal shifts to enforce shift invariance in contrastive learning, achieving state-of-the-art time series classification on six benchmarks plus UCR/UEA archives while cutting training time.