Variational Inference for Heteroscedastic Semiparametric Regression

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Variational Inference: A Review for Statisticians (2016, methodology): “, 2014), semiparametric regression models (Luts et al., 2015; Menictas and Wand, 2015), and nonparametric regression models (Pham et al.”
Semiparametric Mean Field Variational Bayes: General Principles and Numerical Issues (2016, methodology): “For example, the heteroscedastic nonparametric regression model of Menictas and Wand (2015) is such that ordinary mean field variational Bayes is numerically challenging if one uses the same product restrictions as used in homoscedastic nonparametric regression.”
Variational inference for count response semiparametric regression (2013, background): “One of many relevant articles is Michalak et al. (2012), where the need for systems that perform real-time streaming data analyses is described.”
Fully simplified multivariate normal updates in non-conjugate variational message passing (2014, unknown): “Details are given in Menictas and Wand (2014). Figure 2 shows the estimated mean function (fj) contributions, and the standard deviation function (exp(hj/2)) contributions based on both variational approximation”