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Showing 1 to 4 of 4 for “"Variational Bayesian inference"”.
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Disentangling time constant and time dependent hidden state in time series with variational Bayesian inference
… and explore a new model architecture called a Variational Bayes Recurrent Neural Network (VBRNN) for modelling time series. The VBRNN contains explicit structure to disentangle time constant and time dependent dynamics for use with compatible time series, such as those that can be modelled by …
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A Dual Metamodeling Perspective for Design and Analysis of Stochastic Simulation Experiments
… of the computational budget. Third, we propose a variational Bayesian inference-based Gaussian process (VBGP) metamodeling approach to accommodate the situation where either one or multiple simulation replications are available at every design point. VBGP can fit the mean and variance response …
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GAUSSIAN PROCESSES FOR 3D SHAPE MODELLING OF NOISY AND INCOMPLETE DATA. AN APPLICATION TO HUMAN EARS RECONSTRUCTION
… a method for parameter estimation based on Variational Bayesian Inference. Not only do we achieve better registration results in the presence of large regions of missing data, but we provide a more unified way to deal with shape modelling. This is a step towards a more coherent approach and …