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I would like to use the Concrete Dropout Framework from GAL in application to recurrent neural networks. There is a great paper about it and the implementation can be found on the website (Thank you so much Yarin!):

https://github.com/yaringal/ConcreteDropout

He implements a Keras Layer called Concrete Dropout, which can be applied to arbitrairy layers. Nevertheless all his examples are feed forward networks, so here is my question:

Can I use it in a straight forward manner to regularize RNNs?

Example Code in Keras for this would be:

model.add(ConcreteDropout(GRU(32)))
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