… Although PLSA model deals with the issue of multiple topics, each topic model is quite … In
this study, we present a new Bayesian topic mixture model (BTMM) to overcome the burstiness …

… variational Bayesian (VB) algorithms have the weaknesses of low efficiency and poor scalability,
this paper proposes a new distributed stochastic variational inference (… mixture model (…

… Variational inference a review for statisticians[J]. Journal of the American Statistical …
Bayesian estimation of beta mixture models with variational inference[J]. IEEE Transactions on …

… Gaussian mixture filter (GMF) improved by variational Bayesian learning. … estimation of
Gaussian mixture model in non-Gaussian noise environment. By means of variational Bayesian …

… Here we propose a new mixture model to describe the higher-level label image. The formation
of label image is composed of two components: (1) A homogenous and isotropic MRF is …

… Overview of variational inference methods and probabilistic programming of Bayesian
hierarchical models[J]. Railway Computer Application, 2022, 31(3): 6-11. 在线阅读View online: …

… We first extend a finite mixture model to the infinite case by … chain Monte Carlo (MCMC) and
variational inference (VI), has … is given by an independent draw from a Beta(1,α) distribution. …

… Then, RCAR uses a two-component beta-mixture model to divide them into clean and
noise alignments and refurbishes the label according to the posterior probability of the noise-…

… into the probability modeling of the mixture model of the Dirichlet … is obtained by the variational
inference method. An image … 计算获得, 从中可见DPMM 的尺度参数α 以Beta 分布的形状…

… Variational Inference) [40] ,基于stick-breaking表示,将权重边际化以提高推断的准确性和有效性
;随机变分推断(Stochastic Variational Inference) [… (Truncation-Free Variational Inference),截断…