3 citations · 4 across the 3 of their papers we have counts for
3 papers
The FMRIB Variational Bayesian Inference Tutorial II: Stochastic Variational Bayes
Michael A. Chappell, Mark W. Woolrich
Bayesian methods have proved powerful in many applications for the inference of model parameters from data. These methods are based on Bayes' theorem, which itself is deceptively s…
Stochastic Variational Bayesian Inference for a Nonlinear Forward Model
Michael A. Chappell, Martin S. Craig, Mark W. Woolrich
Variational Bayes (VB) has been used to facilitate the calculation of the posterior distribution in the context of Bayesian inference of the parameters of nonlinear models from dat…
Dimensionality reduction for time series data
Diego Vidaurre, Iead Rezek, Samuel L. Harrison +2
Despite the fact that they do not consider the temporal nature of data, classic dimensionality reduction techniques, such as PCA, are widely applied to time series data. In this pa…