Variational Autoencoder: why encoder part predicts log variance?
61480
Why in Variational Auto Encoder (Gaussian variational family) we model $\log\sigma^2$ and not $\sigma^2$ (or $\sigma$) itself?
91193
Natural log approximation
24616
Qualitative variable coding in regression leads to "singularities"
127883
making predictions with log-log regression model
37424
variational question
37786
Variance with minimal MSE in normal distribution
157399
How to interpret the coefficient of variation?
25409
Why does k-fold cross validation generate an MSE estimator that has higher bias, but lower variance then leave-one-out cross-validation?
54989
Why is binary cross entropy (or log loss) used in autoencoders for non-binary data
41356
Reason for square images in deep learning
86569
How to interpret log-linear regression?
88139
Why binary crossentropy can be used as the loss function in autoencoders?
75838
Understanding batch normalization
114124
Variablity in cv.glmnet results
40925
How to perform regression with different error variances
2180
What do the subscripts in expectations mean in loss function
18549
In a Transformer model, why does one sum positional encoding to the embedding rather than concatenate it?