| tslearn-team/tslearn |
2,705 |
|
11 |
38 |
about 2 years ago |
99 |
August 21, 2023 |
127 |
bsd-2-clause |
Python |
| The machine learning toolkit for time series analysis in Python |
| wannesm/dtaidistance |
964 |
|
4 |
23 |
over 2 years ago |
46 |
November 08, 2023 |
21 |
other |
Python |
| Time series distances: Dynamic Time Warping (fast DTW implementation in C) |
| patrickzib/SFA |
258 |
|
0 |
0 |
about 4 years ago |
0 |
|
7 |
gpl-3.0 |
Java |
| Scalable Time Series Data Analytics |
| mblondel/soft-dtw |
235 |
|
0 |
0 |
over 7 years ago |
5 |
May 16, 2018 |
9 |
bsd-2-clause |
Python |
| Python implementation of soft-DTW. |
| asardaes/dtwclust |
232 |
|
3 |
7 |
about 3 years ago |
43 |
February 28, 2023 |
1 |
gpl-3.0 |
R |
| R Package for Time Series Clustering Along with Optimizations for DTW |
| ahwillia/affinewarp |
150 |
|
0 |
0 |
over 2 years ago |
1 |
August 15, 2024 |
4 |
|
Python |
| An implementation of piecewise linear time warping for multi-dimensional time series alignment |
| baggepinnen/DynamicAxisWarping.jl |
89 |
|
0 |
0 |
over 2 years ago |
0 |
|
1 |
other |
Julia |
| Dynamic Time Warping (DTW) and related algorithms in Julia, at Julia speeds |
| hfawaz/aaltd18 |
80 |
|
0 |
0 |
over 7 years ago |
0 |
|
1 |
gpl-3.0 |
Python |
| Data augmentation using synthetic data for time series classification with deep residual networks |
| talcs/simpledtw |
43 |
|
0 |
0 |
about 4 years ago |
0 |
|
0 |
mit |
Python |
| A Python implementation and API for the Dynamic Time Warping (DTW) algorithm |
| dmfolgado/tam |
19 |
|
0 |
0 |
almost 4 years ago |
0 |
|
0 |
mit |
Python |
| Time Alignment Measurement for Time Series |
