STUMPY is a powerful and scalable Python library for modern time series analysis
A Python library for detecting patterns and anomalies in massive datasets using the Matrix Profile
An open-source library of algorithms to analyse time series in GPU and CPU.
The fastest way to compute matrix profiles on CPU and GPU!
golang library for computing matrix profiles along with other time series analysis features
R Functions implementing UCR Matrix Profile Algorithm
Time-series analysis using the Matrix profile in Julia
High-performance time series algorithms for Ruby
An academic project to introduce Dynamic Time Warping (DTW) distance into Matrix Profile.
NATSA is the first near-data-processing accelerator for time series analysis based on the Matrix Profile (SCRIMP) algorithm. NATSA exploits modern 3D-stacked High Bandwidth Memory (HBM) to enable efficient and fast matrix profile computation near memory. Described in ICCD 2020 by Fernandez et al. https://people.inf.ethz.ch/omutlu/pub/NATSA_time-…
This is the core functions needed by the `tsmp` package. The low level and carefully checked mathematical functions are here. These are implementations of the Matrix Profile concept that was created by CS-UCR <http://www.cs.ucr.edu/~eamonn/MatrixProfile.html>.
C# binding for Khiva library.
Time Series Anomaly Detection Solutions for KDD2021 UCR dataset
Matrix Profile 1D subsequence distance profile and top discord anomaly detection
Matrix Profile 1D subsequence distance profile and top discord anomaly detection
PhD Programme in Health Data Science - detecting life-threatening ECG patterns using low-end devices
Publishing and analysing time series on the Semantic Web with Matrix Profile techniques
Contextual anomaly detection tool application in building energy field based on Matrix Profile algorithm
Interactive web app for spatiotemporal decomposition, actionable urban-dynamics statistics, and residual-motif discovery from mobile-phone data — companion tool to Silva, Madeira & Henriques (EPB 2024; Pattern Recognition 2026)
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