Didn’t see it mentioned but good to know about: UCR matrix profile.
The Matrix Profile is honestly one of the most underrated tools in the time series analysis space - it's ridiculously efficient. The killer feature is how it just works for finding motifs and anomalies without having to mess around with window sizes and thresholds like you do with traditional techniques. Solid across domains too, from manufacturing sensor data to ECG analysis to earthquake detection.
The MP is so efficent that you can test ALL window lengths at once! This is called MADRID [a].
[a] Matrix Profile XXX: MADRID: A Hyper-Anytime Algorithm to Find Time Series Anomalies of all Lengths. Yue Lu, Thirumalai Vinjamoor Akhil Srinivas, Takaaki Nakamura, Makoto Imamura, and Eamonn Keogh. ICDM 2023.
I don't think it's being updated. Latest blog posts are from 2020, and Github repos haven't seen commits for the last 5-6 years. MP went a long way since then.
It does convolution of each sub sequence across the series length, and then shows the distance of the closest match.
This can detect both outliers (long distance from closest match) as well as repeated patterns (short distance).
The Matrix Profile is honestly one of the most underrated tools in the time series analysis space - it's ridiculously efficient. The killer feature is how it just works for finding motifs and anomalies without having to mess around with window sizes and thresholds like you do with traditional techniques. Solid across domains too, from manufacturing sensor data to ECG analysis to earthquake detection.
https://www.cs.ucr.edu/~eamonn/MatrixProfile.html