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I saw some implementations of Yoon Kim's Convolutional Neural Network (Paper: http://www.aclweb.org/anthology/D14-1181)....

...in some implementations they put one more Dense(..) Layer before the output layer (with softmax activation). In my opinion there is no additional Dense(..) Layer in the original paper:

So what's the original implementation?

differing Yoon Kim CNN implementations

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Based on the model architecture from original paper below, it looks like there is just one dense layer at the end. Conv layers --> Max Pool over time --> Dense

enter image description here

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    $\begingroup$ I‘m of the same opinion. So would you put the dropout after the flatten()? $\endgroup$ – Predicted Life Oct 8 '19 at 15:52
  • $\begingroup$ Yes, I think dropout comes after flatten. I implemented this in Pytorch, and I used Conv --> Maxpool --> Concat (in this case it is similar to flatten in Keras) --> Dropout --> Dense $\endgroup$ – Tamirlan Oct 8 '19 at 16:34

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