This repository contains synthetic time series data generated using the CauKer framework, as presented in the paper CauKer: Classification Time Series Foundation Models Can Be Pretrained on Synthetic Data.
CauKer is a synthetic data generation framework for pre-training classification Time Series Foundation Models (TSFMs) without relying on real-world data. It combines Gaussian Process (GP)… See the full description on the dataset page:
https://huggingface.co/datasets/paris-noah/CauKer2M.
