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 ![Logo](./figures/TimeCraft2.png)
 
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 # Time Series Generation for Real-World Applications 
 The rapid advancement of artificial intelligence has increasingly emphasized the critical role of time series data in powering intelligent decision-making across diverse domains, including healthcare, finance, energy, and transportation. In these fields, the ability to generate high-quality synthetic time series has become particularly valuable. **Time series generation** technology plays a vital role in alleviating **data scarcity**, especially in scenarios where collecting real-world data is expensive, time-consuming, or impractical. It also enables **privacy-preserving** analysis by producing realistic but non-identifiable synthetic data, reducing the risks associated with sharing sensitive information. Moreover, it supports **simulation and forecasting in risk-free environments**, allowing researchers and practitioners to safely explore hypothetical scenarios and train robust models. Together, these capabilities make time series generation an essential tool for a wide range of real-world applications.