An open-source library of algorithms to analyse time series in GPU and CPU.
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Updated
Sep 3, 2021 - C++
An open-source library of algorithms to analyse time series in GPU and CPU.
Contains an implementation (sklearn API) of the algorithm proposed in "GENDIS: GEnetic DIscovery of Shapelets" and code to reproduce all experiments.
A software package for statistically significant shapelet mining
Code for "Generalised Interpretable Shapelets for Irregular Time Series"
Implementation of the Random Dilated Shapelet Transform algorithm along with interpretability tools. Documentation is WIP on read the docs.
Uncertain Shapelet Transform Classification, a shapelet method for uncertain time series classification
This repo contains useful links to research papers and implementations of shapelets discovery/learning techniques from different sources.
C# binding for Khiva library.
Repository for "Data Mining - Advanced Topics and Applications" projects exam.
Theoretically guaranteed shapelet-learning algorithm
Uncertain times séries classification
Scalable and Accurate Subsequence Transform
Adversarially-Built Shapelets Algorithm
Implementation (VHDL) and verification of the accelerator proposed in the paper "Hardware Accelerator for Shapelet Distance Computation in Time-Series Classification", from May 2020
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