Papers by Tianbao Song

1 papers
Scale-VAE: Preventing Posterior Collapse in Variational Autoencoder (2024.lrec-main)

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Challenge: Variational autoencoder (VAE) is a widely used generative model . but when employing strong autoregressive generation networks, VAE tends to converge to a degenerate local optimum known as posterior collapse.
Approach: They propose a model called Scale-VAE to solve a posterior collapse problem . they use a factor to keep the posterior dimension discriminative across data instances .
Outcome: The proposed model outperforms state-of-the-art models in density estimation and representation learning.

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