fcCovdaddd: Covariance between first and second derivatives from...

In mgoulet847/tagi: Tractable Approximate Gaussian Inference in Neural Networks

Description

This function calculates covariance between activation units and first derivatives and covariance between first and second derivatives from consecutive layers.

Usage

fcCovdaddd(mao, mai, mdai, Caoai, Cdodi, acti, ni, no, B)

Arguments

mao	Mean vector of activation units from next layer
mai	Mean vector of activation units from current layer
mdai	Mean vector of activation units' first derivative from current layer
Caoai	Covariance between activation units from current and next layers
Cdodi	Covariance between derivatives from current and next layers
acti	Activation function index for current layer defined by activationFunIndex
ni	Number of units in current layer
no	Number of units in next layer
B	Batch size

Value

• Covariance between first derivatives from next layer and activation units from current layer

• Covariance between first and second derivatives from consecutive layers

mgoulet847/tagi documentation built on Dec. 21, 2021, 5:10 p.m.