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Regarding GAN and its loss objective

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How to use 'mse' as loss function?
In the example provided, sigmoid is used. How to modify the function to make the loss objective as minimum mse.

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Accepted Answer

Sourav Bairagya
Sourav Bairagya on 16 Dec 2019
You can use 'mse' function from Deep Learning Toolbox which calculates half mean sqaured error between given two inputs.
dlY = mse(dlX,targets);
Format for 'dlX' or 'targets' will be as follows: [height, width, no of channels, no of observations].
'dlX' and 'targets' can be of datatype dlarray or numeric array.
If you want to use whole mse loss, then multiply the output with 2, i.e.
dlY = 2*mse(dlX,targets);
For more information you can leverage this link:

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