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Found 2 papers, 2 papers with code
Interpretable Time-series Classification on Few-shot Samples
Recent few-shot learning works focus on training a model with prior meta-knowledge to fast adapt to new tasks with unseen classes and samples.
Omni-Scale CNNs: a simple and effective kernel size configuration for time series classification
Particularly, it is a set of kernel sizes that can efficiently cover the best RF size across different datasets via consisting of multiple prime numbers according to the length of the time series.
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