#time-series generation

The method outperforms a base latent-flow baseline and prior state of the art on realness and efficiency metrics, making synthetic time series more dependable as training data for forecasting or anomaly-detection work.

For energy analysts and researchers, LoaDiff provides a tool to generate realistic synthetic data for load forecasting and appliance detection, which is valuable when real-world data is restricted.

金融时间序列生成终于有了一个可微的随机卷积特征方案，做量化分析或金融建模的团队可以直接用SOCK替代签名特征，小样本场景下效果更好。