How to build a network consisting of several subnets and a multiplex net?

As shown in the following figure, the framework consists of several view-specific subnets (f1, f2, … , fv) and a multiplex net. (gc).

In the training phase, the loss function needs all the output of ((f1, f2, … , fn). Of course, we have training data for parallel inputting.

However, when it comes to test phase, only one view-specific subnet (ft) is activated for input.:thinking:

Should I build the f1, f2, … , fv within the gc? Or build them alone, and finally combine the parameters in the training phase?

Thank you!


I have met this question too. Thanks!

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