Variational autoencoders are commonly used sequence-to-sequence models that use a probabilistic approach to compress the input data sequence into a latent space and then generate a new sequence.
Variational autoencoders are commonly used sequence-to-sequence models that use a probabilistic approach to compress the input data sequence into a latent space and then generate a new sequence.