Answers.Body: <p>I do not see why this would not be the case. As long as you use a similar batch optimizer the same principle should apply.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2023-03-19T12:24:53.253Z
Answers.LastActivityDate: 2023-03-19T12:24:53.253Z
Answers.UserDisplayName: dorien
Body: <p>Does it make sense to use batch normalization in deep (stacked) or sparse auto-encoders? </p>
  
  <p>I cannot find any resources for that. Is it safe to assume that, since it works for other DNNs, it will also make sense to use it and will offer benefits on training AEs?</p>
  
Tags: <deep-neural-networks><autoencoders><batch-normalization>
Title: Does it make sense to use batch normalization in deep (stacked) or sparse auto-encoders?
UserDisplayName: Glrs
ThreadText: # Does it make sense to use batch normalization in deep (stacked) or sparse auto-encoders?
  
  (Asked by: username_0 on 2018-07-23)
  
  Does it make sense to use batch normalization in deep (stacked) or sparse auto-encoders?
  
  I cannot find any resources for that. Is it safe to assume that, since it works for other DNNs, it will also make sense to use it and will offer benefits on training AEs?
  
  **Tags:** deep-neural-networks, autoencoders, batch-normalization
  
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  ## 1 answers
  
  ### Answer by username_1 on 2023-03-19. Score: 0
  
  I do not see why this would not be the case. As long as you use a similar batch optimizer the same principle should apply.
  
  
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