Neural networks trained on simulated time series learn to cluster real data using features like autocorrelations, matching or exceeding traditional methods and sometimes auto-selecting the number of clusters.
(1990), ‘A distance measure for classifying arima models’,Journal of Time Series Analysis 11(2), 153–164
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Amortized Neural Clustering of Time Series based on Statistical Features
Neural networks trained on simulated time series learn to cluster real data using features like autocorrelations, matching or exceeding traditional methods and sometimes auto-selecting the number of clusters.