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nbro
nbro
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For example, AFAIK, the pooling layer in a CNN is not differentiable, but it can be used because it's not learning. Is it always true?

For example, AFAIK pooling layer in CNN is not differentiable, but it can be used because it's not learning. Is it always true?

For example, AFAIK, the pooling layer in a CNN is not differentiable, but it can be used because it's not learning. Is it always true?

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RedRus
RedRus
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Can non-differentiable layer be used in a neural network, if it's not learned?

For example, AFAIK pooling layer in CNN is not differentiable, but it can be used because it's not learning. Is it always true?