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