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In-Context Time Series Classification with Random Convolutional Features
Time series classification is central to domains like medical signal analysis, industrial monitoring, and sensor based activity recognition, where class information manifests as localized shapes, specific frequencies, temporal shifts, or complex cross channel interactions. Random convolutional transforms efficiently map these sequences to fixed dimensional tabular features but are traditionally paired with simple ...