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For questions related to deep neural networks, which are artificial neural networks with "many" layers, where "many" can vary depending on the context.

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Does it make sense to use batch normalization in deep (stacked) or sparse auto-encoders?

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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