DTWSpeech

The machine learning toolkit for time series analysis in Python

aeneas is a Python/C library and a set of tools to automagically synchronize audio and text (aka forced alignment)

Time series distances: Dynamic Time Warping (fast DTW implementation in C)

Python implementation of KNN and DTW classification algorithm

Python implementation of soft-DTW.

Transfer learning for time series classification

[AAAI2023] A PyTorch implementation of PDFormer: Propagation Delay-aware Dynamic Long-range Transformer for Traffic Flow Prediction.

Dynamic Time Warping (DTW) and related algorithms in Julia, at Julia speeds

Formed trajectories of sets of points.Experimented on finding similarities between trajectories based on DTW (Dynamic Time Warping) and LCSS (Longest Common SubSequence) algorithms.Modeled trajectories as strings based on a Grid representation.Benchmarked KNN, Random Forest, Logistic Regression classification algorithms to classify efficiently trajectories.

A GP-GPU/CPU Dynamic Time Warping (DTW) implementation for the analysis of Multivariate Time Series (MTS).