16 citations · 40 across the 8 of their papers we have counts for
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stat.ML2017
On parameters transformations for emulating sparse priors using variational-Laplace inference
Jean Daunizeau
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. Sparsity constraints can…
stat.ML2017★ 13 cited
Semi-analytical approximations to statistical moments of sigmoid and softmax mappings of normal variables
Jean Daunizeau
This note is concerned with accurate and computationally efficient approximations of moments of Gaussian random variables passed through sigmoid or softmax mappings. These approxim…
stat.ME2017★ 16 cited
The variational Laplace approach to approximate Bayesian inference
Jean Daunizeau
Variational approaches to approximate Bayesian inference provide very efficient means of performing parameter estimation and model selection. Among these, so-called variational-Lap…