Published On: August 15th, 2024Categories: AI News

VAE for Time Series. Generate realistic sequential data with… | by Da...

Convolutions exploit the cyclical nature of the inputs to build better latent features. Deconvolutions convert latent features into overlapping, repeating sequences to generate data with periodic patterns.

Flexible Time Dimension

Image-generating VAEs usually have thousands of images pre-processed to have a fixed width and height. The generated images will match the width and height of the…

https://towardsdatascience.com/vae-for-time-series-1dc0fef4bffa?gi=3628542e5a5a&source=rss—-7f60cf5620c9—4
towardsdatascience.com

Feed Name : Towards Data Science – Medium

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hashtags : #VAE #Time #Series #Generate #realistic #sequential #data #Da..

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