SAURL-TS: A Self-Adaptive Framework for Unsupervised Time Series Representation Learning

This repository contains the code for SAURL-TS, a framework for unsupervised time series representation learning.

Requirements

We use Python 3.9. The main packages include:

• numpy
• scikit-learn
• torch
• matplotlib
• pandas

You can install the necessary dependencies with:

pip install -r requirements.txt

Usage

To train the model, run the following command:

python train.py

Project Structure

├── datasets/                 # Directory for datasets
├── models/                   # Directory for models
├── tasks/                    # Directory for downstream task
├── config.py                 # Configuration file for tasks
├── data_load.py              # Script for loading datasets
├── requirements.txt          # Python packages
├── saurl_ts.py               # Main SAURL-TS model file
├── train.py                  # Main training script
├── utils.py                  # Utility functions
└── README.md                 # Documentation

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