@Shisho_Sama
Do you know the theoretical reason why BCE, MSE is suited for VAE / AE loss function.
I found these article or paper saying like

’ it is usually used ’

or

’ There are two common loss functions used for training autoencoders, these include the mean-squared error (MSE) and the binary cross-entropy (BCE) ’

But I really don’t get why channel-wise cross entropy is not suited in my case.

  
      
      arXiv.org
  
  
    

On denoising autoencoders trained to minimise binary cross-entropy 8

Denoising autoencoders (DAEs) are powerful deep learning models used for
feature extraction, data generation and network pre-training. DAEs consist of
an encoder and decoder which may be trained simultaneously to minimise a loss
(function) between an...


  
  
    
    
  
  



  
      stats.stackexchange.com
  
  
      
    
  

  Why is binary cross entropy (or log loss) used in autoencoders for non-binary data 13



  loss-functions, tensorflow, autoencoders, cross-entropy



  asked by
  
  
    Flek
  
  on 11:51PM - 26 Feb 19 UTC