Bayesian subspace multinomial model learns Gaussian posterior document embeddings, and a Gaussian classifier that exploits their covariance improves topic identification.
i-Vectors in Language Modeling: An Efficient Way of Domain Adaptation for Feed-Forward Models,
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Learning document embeddings along with their uncertainties
Bayesian subspace multinomial model learns Gaussian posterior document embeddings, and a Gaussian classifier that exploits their covariance improves topic identification.