I understand that the forward operation of transpose convolution is similar to the backward operation of regular convolution, and vice versa, as it relates to determining Z[l] (forward) or dA[l-1] (backward). I also know that the gradients of the weights and biases are also measured during the back …

What do you mean by “transpose convolution”? Regarding your question, Yes, the parameters are updated during the back prob with the following formula: W = W - \alpha dW b = b - \alpha db

Transpose convolution in a CNN. Upsampling an image during the expansion phase of U-net. I’m looking for a specific definition of dW and db.

Transpose convolution backprop question

Course Q&A Deep Learning Specialization Convolutional Neural Networks

saifkhanengr May 24, 2024, 1:30pm 4

Alright. There are several threads on gradients. Check these threads: one, two, and three.

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Transpose convolution backprop question

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