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Found 3 papers, 2 papers with code
Never a Dull Moment: Distributional Properties as a Baseline for Time-Series Classification
The variety of complex algorithmic approaches for tackling time-series classification problems has grown considerably over the past decades, including the development of sophisticated but challenging-to-interpret deep-learning-based methods.
Feature-Based Time-Series Analysis in R using the theft Package
With an increasing volume and complexity of time-series datasets in the sciences and industry, theft provides a standardized framework for comprehensively quantifying and interpreting informative structure in time series.
An Empirical Evaluation of Time-Series Feature Sets
For example, in TSFEL, 90% of the variance across 390 features can be captured with just four PCs.
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