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JackMedley commented Aug 22, 2016

Hi Rajiv,
Can I ask what the purpose of the dropout layer is in a problem such as this? When training for something like addition don't we need to know all of the inputs?

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rajshah4 commented Aug 27, 2016

Hmm, its a good question. This was one of my first RNNs and I just grabbed code from other projects. I am thinking that it would work like dropout generally, it would help against overfitting and get a better sense of how addition works. If you have the time, I would be curious if you played around with the dropout whether it works like that.

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