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Found 5 papers, 0 papers with code
Dynamic causal modelling of COVID-19
This technical report describes a dynamic causal model of the spread of coronavirus through a population.
Variational Bayesian modelling of mixed-effects
This note is concerned with an accurate and computationally efficient variational bayesian treatment of mixed-effects modelling.
On parameters transformations for emulating sparse priors using variational-Laplace inference
So-called sparse estimators arise in the context of model fitting, when one a priori assumes that only a few (unknown) model parameters deviate from zero.
The variational Laplace approach to approximate Bayesian inference
Variational approaches to approximate Bayesian inference provide very efficient means of performing parameter estimation and model selection.
Semi-analytical approximations to statistical moments of sigmoid and softmax mappings of normal variables
This note is concerned with accurate and computationally efficient approximations of moments of Gaussian random variables passed through sigmoid or softmax mappings.
