For questions related to the pooling (aka downsampling or subsampling) operation/layers, in particular, in the context of convolutional neural networks. There are also specific tags for max-pooling and average pooling.
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Can non-differentiable layer be used in a neural network, if it's not learned?Is pooling a kind of dropout?
What is the effect of using pooling layers in CNNs?
Is a non-linear activation function needed if we perform max-pooling after the convolution layer?
Is down-sampling the only purpose of using stride?
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