Protected: Calculation of marginal likelihood, posterior mean, posterior covariance, and predictive distribution using variational Bayesian methods
Methods for computing marginal likelihoods, posterior means, posterior covariances, and predictive distributions in variational Bayesian methods for digital transformation, artificial intelligence , and machine learning tasks James Stein estimator, maximum likelihood estimation, empirical Bayes estimator, Bayesian free energy, hyperparameters, automatic relevance determination, linear regression models, stochastic complexity, log marginal likelihood empirical Bayesian learning, multinomial distribution models, posterior means, linear regression models