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Found 3 papers, 1 papers with code
A Spectral Enabled GAN for Time Series Data Generation
uTSGAN showed to outperform TSGAN in 80\% of the data sets by the same number of training epochs and 60\% of the data sets in 3/4th the amount of training time or less while maintaining the few shot generation ability with better FID scores across those data sets.
Conditional GAN for timeseries generation
It is abundantly clear that time dependent data is a vital source of information in the world.
A Category Space Approach to Supervised Dimensionality Reduction
To this end, we set up a model in which each class is represented as a 1D subspace of the vector space formed by the features.
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