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Autoencoding variational Bayes for latent Dirichlet allocation
South African Forum for Artificial Intelligence Research
Many posterior distributions take intractable forms and thus require variational inference where analytical solutions cannot be found. Variational Inference and Monte Carlo Markov Chains (MCMC) are established mechanism to approximate these intractable values. An alternative approach to sampling and optimisation for approximation is a direct mapping between the data and posterior distribution. This is made possible by recent advances in deep learning methods. Latent Dirichlet Allocation (LDA)dblp:conf/fair2/WolpeW19 fatcat:pw2alommoba7fgth5hegsaqhei