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Results indicate that recursive quantum feature transformations can improve stability and out-of-sample performance for compact hybrid quantum--classical temporal models.
A unified toolbox for time-series dataset similarity could revolutionize how researchers select and evaluate datasets for AI model fine-tuning.
