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- $\begingroup$ Please ask only one question per post. Also, i'ts unclear what you mean by "the most important features of addition vs multiplication", and it's not clear how you are using addition or multiplication, so I don't think any of these questions are answerable in their current form. If you can edit your question to address this feedback, I encourage you to do so. $\endgroup$D.W.– D.W.2019-02-16 21:46:11 +00:00Commented Feb 16, 2019 at 21:46
- $\begingroup$ I don't quite understand this, but typically you're using dense layers for non-linear transformations. If all it does is sum combinations of inputs, it's a linear transformation. That almost surely defeats the purpose of what you're using it for. $\endgroup$Sean Owen– Sean Owen2019-02-17 00:56:43 +00:00Commented Feb 17, 2019 at 0:56
- $\begingroup$ dear @SeanOwen, I explained that in a specific part of the network there are two tensors which have to unify in order to feed into the next layer, in this case, there are several choices. one of these choices is basic mathematics operation such as addition, multiplication. we performed several experiments with each of these operations. I change the question and make it narrow. could u look at it again? $\endgroup$amoioioi– amoioioi2019-02-17 08:14:44 +00:00Commented Feb 17, 2019 at 8:14
- $\begingroup$ Dear @D.W., I change the question, I used basic addition which is provided by Tensorflow, tf.math.add which returns the a+b element-wise (each of a and b is equal tensors) and for multiplication I also used the tf.math.multiply function. $\endgroup$amoioioi– amoioioi2019-02-17 08:26:54 +00:00Commented Feb 17, 2019 at 8:26
- 1$\begingroup$ What do you mean 'unify'? there is no general answer to this. Which operation you use depends on what you are trying to do, and, practically, which one works better. If you mean to add things, you add them. $\endgroup$Sean Owen– Sean Owen2019-02-17 15:36:48 +00:00Commented Feb 17, 2019 at 15:36
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