Papers by Runzhi Tian

1 papers
Learning VAE-LDA Models with Rounded Reparameterization Trick (2020.emnlp-main)

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Challenge: No reparameterization form of Dirichlet distributions is known to date for topic models .
Approach: They propose a method to reparameterize Dirichlet distributions for the learning of VAE-LDA models by using a latent Dirichlets prior.
Outcome: The proposed method outperforms existing neural topic models on benchmark datasets and on a synthetic dataset.

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