fcCovwdowdi2: Covariance between next layer product and current layer...
In mgoulet847/tagi: Tractable Approximate Gaussian Inference in Neural Networks
Description
Usage
Arguments
Value
Description
This function calculates covariance cov(wdo,(wdi)^2) of weights times derivatives
products terms when there are one product in next layer and two squared in current.
Usage
1
fcCovwdowdi2(mpdi, Cdgoddgik)
Arguments
mpdi
Mean vector of first derivative product wd of current layer
Cdgoddgik
Covariance between weights times derivatives from consecutive layers
Value
Covariance cov(wdo,(wdi)^2) of weights times derivatives products terms when there is one product in next layer and two squared in current
mgoulet847/tagi documentation built on Dec. 21, 2021, 5:10 p.m.
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Description Usage Arguments Value
Description
This function calculates covariance cov(wdo,(wdi)^2) of weights times derivatives products terms when there are one product in next layer and two squared in current.
Usage
1 | fcCovwdowdi2(mpdi, Cdgoddgik)
|
Arguments
mpdi |
Mean vector of first derivative product wd of current layer |
Cdgoddgik |
Covariance between weights times derivatives from consecutive layers |
Value
Covariance cov(wdo,(wdi)^2) of weights times derivatives products terms when there is one product in next layer and two squared in current
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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